Bifurcation analysis of the Microscopic Markov Chain Approach to contact-based epidemic spreading in networks
Chaos, Solitons and Fractals
; 166, 2023.
Article
in English
| Scopus | ID: covidwho-2238754
ABSTRACT
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. © 2022 Elsevier Ltd
Bifurcation (mathematics); COVID-19; Dynamical systems; Epidemiology; Markov processes; Bifurcation analysis; Compartmental modelling; Discrete maps; Endemic state; Epidemic spreading; In networks; Infectious disease; Markov chain approaches; Second-order phase transition; Transcritical bifurcation; Complex networks; Discrete-map
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
Chaos, Solitons and Fractals
Year:
2023
Document Type:
Article
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