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Nonlinear dynamic analysis of an epidemiological model for COVID-19 including public behavior and government action (preprint)
arxiv; 2020.
Preprint
in English
| PREPRINT-ARXIV | ID: ppzbmed-2006.09530v2
ABSTRACT
This paper is concerned with nonlinear modeling and analysis of the COVID-19 pandemic currently ravaging the planet. There are two objectives:
to arrive at an appropriate model that captures the collected data faithfully, and to use that as a basis to explore the nonlinear behavior. We use a nonlinear SEIR (Susceptible, Exposed, Infectious & Removed) transmission model with added behavioral and government policy dynamics. We develop a genetic algorithm technique to identify key model parameters employing COVID19 data from South Korea. Stability, bifurcations and dynamic behavior are analyzed. Parametric analysis reveals conditions for sustained epidemic equilibria to occur. This work points to the value of nonlinear dynamic analysis in pandemic modeling and demonstrates the dramatic influence of social and government behavior on disease dynamics.
Full text:
Available
Collection:
Preprints
Database:
PREPRINT-ARXIV
Language:
English
Year:
2020
Document Type:
Preprint
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