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With a didactic interest, we analyze the effects of using delays of different orders in the Industrial Dynamics models. We determine the analytical and numerical solutions for a simple case. Second, we consider a deterministic continuous inventory model. Through the stability analysis of differential equations, we show that the incorporation of delays of second order or higher does not necessarily improve the response of the system, but rather introduces solutions that are not desirable with respect to the real behavior. With this simple example, we highlight the importance of being careful in the construction of the models to avoid the appearance of unwanted dynamic behaviors. [ABSTRACT FROM AUTHOR]

As a result of the pandemic, scientists from many countries joined forces to study the behavior of the virus and predict the evolution of the pandemic. Through Industrial Dynamics, we propose a mathematical model to study the spread of the COVID-19 disease, which occurred in Rosario, Argentina. Therefore, this presentation is intended to be a training tool to analyze the dynamics of the pandemic. We study the stability of the model and reduce the problem to a first-order autonomous differential equation. We establish a strategy to determine the parameters of the system. The numerical simulations reproduce the experimental data with reasonable precision, which validates the model and makes it possible to predict the dynamics of the infection considering various health measures. [ABSTRACT FROM AUTHOR]