Nonlinear adaptive control of tuberculosis with consideration of the risk of endogenous reactivation and exogenous reinfection.
Tuberculosis is one of deadly diseases in many countries that attacks to the human body and causes damage to the lung, causing bloody coughing and if left untreated, it will kill half of the affected people. Tuberculosis bacteria can stay latent and reactivate after passing appropriate conditions. For this reason, control of this disease and treatment of infected people has a significant importance, and observing health issues can prevent the spread of it. In this paper, a nonlinear adaptive control method is proposed for the first time in order to control and treat tuberculosis outbreak subjected to the modeling uncertainty. To design a control system being robust against uncertainties, an adaptation law is defined to update values of estimated parameters and ensures the whole system stability. The treatment achievement and stability of the closed-loop system is proved by the Lyapunov theorem and confirmed by some simulations. The proposed strategy has the capability to control the tuberculosis outbreak by reducing the numbers of active infectious and persistent latent individuals based on their desired values in the society.
['Nematollahi|Mohammad Hassan|MH|', 'Vatankhah|Ramin|R|', 'Sharifi|Mojtaba|M|']
D004196:Disease Outbreaks D006801:Humans D000084063:Reinfection D014376:Tuberculosis D035501:Uncertainty
Adaptive control Tuberculosis Exogenous reinfection Epidemic disease Lyapunov stability Nonlinear control