ABSTRACT
In general, a psychological disorder is a syndrome with significant rapid variability in control of emotions, cognitive control, and behaviors that reflect dysfunction in the biological, psychological, or development process underlying the function of cognitive behavior. Psychological disorders are occurring more prominently in post-COVID-19 patients. This work aims to investigate a detailed literature review on psychological disorders and mathematical models of the system to predict and forecast the psychological and mental illnesses and the spread of COVID-19 during the pandemic. A systematic statistical analysis was more appreciable to determine the significant level to suggest an appropriate medical direction to overcome the psychological disorders. The mathematical models, such as the system dynamics model used to predict the growth rate and causes of the various disorders such as depression, bipolar disorder, eating disorders, personality disorders, stress disorders, psychotic disorders, etc., propose the medical precautions and treatment methods for the dynamic combination of psychological disorder patients effectively with a systematic approach. Further, the extended work on machine learning approaches enhances its accuracy. It matches the scenario in real-time to predict the effects of disorders in post-COVID-19 patients. A set of massive data from the open-source will substantiate the model's effectiveness in predicting disorders of various levels and simulate the data using the system dynamics model using VenSim to foresee its future growth rate to design and develop the methodology to minimize the psychological disorders. The planned contents are: stating the various psychological disorders, mapping the psychological disorders of post-COVID patients with the standard, and work performed in the multimodal analysis of psychological analysis in the literature to date with the mapped psychological disorders. A questionnaire survey from doctors on psychological disorders was quantified and analyzed using statistical methods. Various mathematical models, such as Markov chain, Monte Carlo simulation, SIR model, and simulation models of multimodal analysis of psychological disorders, substantiate the model using the system dynamics using the VenSim package to predict the effects. Using open-source data, the researchers proved the accuracy of the computational modelling and stochastic mathematical modelling results in building the models to predict the disorders and viable proposed solutions for patients' healthy well-being by minimizing the effect of the disorder at the earliest. © 2022 Nova Science Publishers, Inc. All rights reserved.