Compartmental modeling approach for prediction of unreported cases of COVID-19 with awareness through effective testing program

The objective of this article is to study the compartmental modeling approach for the prediction of unreported cases of coronavirus disease 2019 by considering six compartments. Our model is described by a system of six ordinary differential equations with initial conditions. The basic properties of solution of the model are established. The model is shown to have two equilibrium points, i.e., the disease-free and endemic equilibrium points. The basic reproduction number R0{R}_{0} is derived by the next-generation matrix method. Stability analysis is carried out in the study. Furthermore, sensitivity analysis is also performed to identify the impact of important parameters that significantly affect R0{R}_{0}. Numerical simulations provide a good approximation model for COVID-19, which will be utilized to investigate future pandemic with similar nature of spread as COVID-19 and estimate the number of unreported cases worldwide.