Pulmonary Tuberculosis and Pneumonia Co-Dynamics: A Mathematical Modelling Approach

This study presents a novel mathematical model that captures the co-dynamics of pulmonary tuberculosis in the presence of opportunistic pneumonia. The model integrates opportunistic pneumonia into the classical pulmonary tuberculosis transmission framework, based on clinical evidence of a lethal synergism between the two diseases. A Holling-type saturation function is utilized to reflect the impact of natural immunity on the progression from latent tuberculosis infection to active disease. Asymptomatic infectious individuals can transmit the infection unnoticed, thereby significantly contributing to the high rate of transmission. Thus, the screening of asymptomatic individuals is incorporated into the model as a strategy to mitigate the prevalence of co-infections. A comprehensive sensitivity analysis and numerical simulations were conducted to evaluate the effects of various interventions, including enhancing natural immunity, screening asymptomatic and latently infected individuals, improving vaccine efficacy, and treating patients with severe pulmonary tuberculosis. The sensitivity analysis reveals that improving vaccine efficacy is the most effective strategy for minimizing co-infections. Simulations also demonstrate that increased screening and treatment rates significantly reduce the burden of pulmonary tuberculosis-pneumonia co-infections. These results underscore the need to develop vaccines with higher efficacy to reduce co-infections of pulmonary tuberculosis and opportunistic pneumonia. Additionally, the study recommends expanded screening of asymptomatic tuberculosis cases and the strengthening of immunity among latently infected populations.