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Preprint in English | medRxiv | ID: ppmedrxiv-20063354


This paper presents open-source computer simulation programs developed for simulating, tracking, and estimating the COVID-19 outbreak. The programs consist of two separate parts: one set of programs built in Simulink with a block diagram display, and another one coded in MATLAB as scripts. The mathematical model used in this package is the SIR, SEIR, and SEIRD models represented by a set of differential-algebraic equations. It can be easily modified to develop new models for the problem. A generalized method is adopted to simulate worldwide outbreaks in an efficient, fast, and simple way. To get a good tracking of the virus spread, a sum of sigmoid functions was proposed to capture any dynamic changes in the data. The parameters used for the input (infection and recovery rate functions) are computed using the parameter estimation tool in MATLAB. Several statistic methods were applied for the rate function including linear, mean, root-mean-square, and standard deviation. In addition, an adaptive neuro-fuzzy inference system is employed and proposed to train the model and predict its output. The programs can be used as a teaching tool and for research studies.