Related Experiment Video
Updated: Dec 11, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Nonlinear dynamic analysis of an epidemiological model for COVID-19 including public behavior and government action
C A K Kwuimy1, Foad Nazari2, Xun Jiao2
1Department of Engineering Education, University of Cincinnati, Cincinnati, OH USA.
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 susceptible, exposed, infectious and removed transmission model with added behavioral and government policy dynamics. We develop a genetic algorithm technique to identify key model parameters employing COVID-19 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.
Related Concept Videos
Steps in Outbreak Investigation
Causality in Epidemiology
Statistical Methods for Analyzing Epidemiological Data
Mechanistic Models: Compartment Models in Individual and Population Analysis
Exponential Equations for Modeling Growth
Population Growth

