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                  <mods:namePart>Arenas, Alex</mods:namePart>
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                  <mods:namePart>Garijo, Antoni</mods:namePart>
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                  <mods:namePart>Gómez, Sergio</mods:namePart>
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                  <mods:namePart>Villadelprat Yagüe, Jordi</mods:namePart>
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                  <mods:dateIssued encoding="iso8601">2023</mods:dateIssued>
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               <mods:abstract>Altres ajuts: Universitat Rovira i Virgili, Spain (2019PFR-URV-B2-41); ICREA AcademiaThe 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.</mods:abstract>
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               <mods:accessCondition type="useAndReproduction">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/</mods:accessCondition>
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                  <mods:title>Bifurcation analysis of the Microscopic Markov Chain Approach to contact-based epidemic spreading in networks</mods:title>
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