Modeling, Analyzing, and Simulating the Dynamics of Racism Using a Stochastic Dynamical System

Racism is a complex issue rooted in the historical Atlantic slave trade, which has led to inequalities and social instability. This study developed a stochastic mathematical model to analyze the dynamics, prevention, and control of racism. The entire population was categorized into susceptible, protected (those who deny racism), racist (those who propagate racism), jailed, and removal groups. The average number of racists caused by a single racist person was computed using stochastic perturbation and Ito’s principle, yielding a numerical value of . This suggests that the endemic equilibrium point of the model is globally stable and provides insights for minimizing the propagation of racism. The study presented numerical simulations graphically using MATLAB software to examine the influence of key parameters. It was suggested that increasing the rate of being caught and imprisoned due to racism ( δ ), the protected rate ( θ ), and the removal rate ( γ ), as well as reducing the racist contact rate ( α ), can help minimize the basic reproductive number, leading to reduced propagation of racism. The importance of addressing influencing factors and taking appropriate measures to control racism effectively was emphasized, highlighting the role of denying racism in reducing its spread and promoting social equality.