Mathematical Model for COVID-19 pandemic with implementation of intervention strategies and Cost-Effectiveness Analysis

Abstract

In this study, a novel mathematical model for the dissemination dynamics of COVID-19 is developed. The main objective is to analyze the effectiveness of pharmaceutical interventions in lowering the COVID-19 contagions. We first demonstrate the positivity and boundedness of the solutions of the model and then compute the fundamental reproduction number. The stability analysis of contagion-free equilibrium is performed. The model is fitted to the COVID-19 reported data for a period of twelve months in India and estimate three parameters. The sensitivity analysis is conducted to identify the significant factors which impact the COVID-19 disease prevalence. We then define an optimum control problem using pharmaceutical interventions vaccination and treatment as the control functions to minimize the dissemination of COVID-19 contagions and disease-related mortality. Cost-effectiveness analysis is employed to determine the most effective and least costly strategy. The results are determined that the combination of vaccination and treatment is the most effective and least costly strategy in mitigating the spread of COVID-19 contagions. Furthermore, the impact of different levels of vaccine efficacy on contagion trajectories is examined, and it is shown that COVID-19 contagions and disease related fatalities would decrease as vaccination efficacy increases. The outcomes would assist administrators in developing efficient strategies to reduce the scope of the COVID-19 pandemic.

Keywords

• COVID-19
• Sensitivity analysis
• Vaccine efficacy
• Vaccine coverage
• Optimal control problem
• Cost effectiveness