Comparative Exploration of Tuberculosis Transmission in High-Risk and Low-Risk Populations by Enhanced Numerical Algorithm
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Abstract
This study compares the transmission of tuberculosis (TB) in high and low-risk populations by employing the 6th Order Runge-Kutta algorithm and the Susceptible-Vaccinated-Exposed-Infected (SVEI) model. Mycobacterium tuberculosis, the bacterium causing TB, is a global health concern with varying incidence among different demographic groups. Our research focuses on two distinct populations: high-risk individuals, who have had greater exposure to TB, and low-risk persons with minimal contact. The SVEI model is used to depict the dynamics of TB transmission, considering variables such as vaccination and latency duration. In this study, we introduce a novel methodology that considers only the true positives in each SVEI model category. This approach involves accounting solely for those accurately classified as susceptible, immunized, exposed, or infected, utilizing the sixth-order Runge-Kutta method. By employing this method, we can forecast future trends in TB transmission in both populations. Preliminary findings reveal significant differences in the dynamics of TB transmission between high- and low-risk populations. These results could potentially impact public health strategies for TB control by emphasizing the necessity of targeted interventions that consider population-specific risk levels. However, further investigation is necessary to validate these conclusions.
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