Optimal control and cost-effectiveness analysis for COVID-19 and tuberculosis co-infection model

This study investigates the complex interplay between COVID-19 and tuberculosis (TB) through a deterministic compartmental model, capturing the dynamics of single and co-infection transmission. The basic reproduction number is derived for each disease independently and within the co-infection framework. We analyze the disease-free and endemic equilibria, assess global stability, and explore bifurcation behaviour. A sensitivity analysis is conducted to identify key parameters influencing the spread of infection. To obtain control strategies, we develop an optimal control framework incorporating four interventions aimed at reducing disease prevalence. Additionally, a cost-effectiveness analysis is performed to assess the economic viability of these strategies. The results demonstrate that combined interventions significantly reduce the overall co-infection burden. In particular, strategy that enhance TB screening and promote early diagnosis emerges as the most cost-effective, especially in light of the large proportion of undetected TB cases. These findings underscore the critical need for strengthened surveillance, integrated disease management, and the implementation of cost-effective public health policies to mitigate the dual burden of TB and COVID-19.