(untitled) (European Journal of Pure and Applied Mathematics, 2025)
The respiratory disease COVID-19 is brought on by a mutagenic ribonucleic acid (RNA) virus. Variants with various traits that could potentially impact transmissibility started to appear globally in December 2020. We develop and examine a computational model of two-strain COVID-19 transmission behaviors in order to deal with this novel aspect of the disease. After a theoretical analysis, enough criteria are derived for the stability of the model’s equilibrium. The model contains single-strain 1 and variant 2 endemic equilibria as well as disease-free and endemic equilibria. The global stability of the model equilibrium is demonstrated using the Lyapunov function. For each strain, we separately compute the basic reproductive numbers R_01 <1, and R_02<1. To determine the realistic values of the model parameters, the actual data from South Africa for the period of three months, are taken into consideration. Sensitivity study employing the partial rank correlation coefficient technique (PRCC) to look into the key variables that affect R_01 <1, or R_02<1 decrease or increase. We show the numerical simulation of the model using non-standard finite difference scheme (NSFDS) and Caputo fractional derivative for distinct non-integer order. The world health organizations (WHO) recommends standard operating procedures (SOPs) to minimize infection in the population. Based on these recommendations, some graphical results for the model with sensitive parameters are provided.