Optimal Control of Tuberculosis: A Review

TL;DR

This paper reviews the application of optimal control theory to tuberculosis models, demonstrating how strategies can be optimized to reduce infectious cases cost-effectively.

Contribution

It introduces a framework for applying optimal control to TB dynamics, including problem formulation and solution, with simulation results showing effectiveness.

Findings

Significant reduction in infectious individuals through optimized strategies

Cost-effective implementation of control measures

Validation via simulations demonstrating practical benefits

Abstract

We review the optimal control of systems modeling the dynamics of tuberculosis. Time dependent control functions are introduced in the mathematical models, representing strategies for the improvement of the treatment and cure of active infectious and/or latent individuals. Optimal control theory allows then to find the optimal way to implement the strategies, minimizing the number of infectious and/or latent individuals and keeping the cost of implementation as low as possible. An optimal control problem is proposed and solved, illustrating the procedure. Simulations show an effective reduction in the number of infectious individuals.