Assessing the Efffects of Vaccination on Tuberculosis and COVID-19 Co-Infection Modelling (Contemporary Mathematics, 2024)
In this paper, an epidemiological model is proposed to study the dynamics of coinfection diseases (TB) and COVID-19 with the effect of vaccination. Tuberculosis (TB) and COVID-19 both are infectious diseases that pose significant global health challenges. Evidence suggests that individuals with TB have a higher risk of acquiring the COVID-19 infection. With the emergence of the COVID-19 pandemic, concerns have arisen regarding the potential impact of the concomitant presence of TB and COVID-19. The epidemiological model is qualitatively analysed using stability analysis theory. The dynamic system exhibits a stable endemic equilibrium point while R0 < 1 and unstable when R0 > 1. The Lyapunov function is used to investigate the global stability of an endemic equilibrium point. The sensitivity analysis is carried out to identify the effective parameters that have the greatest influence on the reproduction number. Numerical results are carried out to assess the effect of various biological parameters in the dyanamic of both coinfection classes of TB & COVID-19. This study aims to analyze the implications of these concurrent diseases and predict the effect of vaccination in managing their coexistence. Our simulation results show that both the coinfection disease TB and COVID-19 can be reduced by increasing rate of vaccination.
Keywords: TB; COVID-19; vaccination; sensitivity analysis