A non-homogeneous Markov early epidemic growth dynamics model. Application to the SARS-CoV-2 pandemic

DOI10.1016/j.chaos.2020.110297zbMath1490.92071OpenAlexW3087334569WikidataQ100298328 ScholiaQ100298328MaRDI QIDQ2123037

Verónica Moreno, Gabriel Pena, Néstor Ruben Barraza

Publication date: 7 April 2022

Published in: Chaos, Solitons and Fractals (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.chaos.2020.110297

zbMATH Keywords

basic reproduction numbercontagionMarkoveffective reproduction numberinfection rateSARS-CoV-2pure birth processdisease spreadingimmunization ratemean time between infections

Mathematics Subject Classification ID

Epidemiology (92D30) Continuous-time Markov processes on general state spaces (60J25) Applications of branching processes (60J85) Medical epidemiology (92C60)

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Uses Software

• GitHub

Cites Work

• Unnamed Item
• An introduction to mathematical modeling of infectious diseases
• Approximation of epidemics by inhomogeneous birth-and-death processes
• Inference of the generalized-growth model via maximum likelihood estimation: a reflection on the impact of overdispersion
• A stochastic SIR epidemic model with Lévy jump and media coverage
• Analysis of stochastic delayed SIRS model with exponential birth and saturated incidence rate
• SIR epidemics with stochastic infectious periods
• An Introduction to Markov Processes
• A communication channel modeled on contagion

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