Cristiana J. Silva

Optimal control for a tuberculosis model with reinfection and post-exposure interventions.

We apply optimal control theory to a tuberculosis model given by a system of ordinary differential equations. Optimal control strategies are proposed to minimize the cost of interventions, considering reinfection and post-exposure interventions. They depend on the parameters of the model and reduce effectively the number of active infectious and persistent latent individuals. The time that the optimal controls are at the upper bound increase with the transmission coefficient. A general explicit expression for the basic reproduction number is obtained and its sensitivity with respect to the model parameters is discussed. Numerical results show the usefulness of the optimization strategies.

Optimal control strategies for tuberculosis treatment: A case study in Angola

We apply optimal control theory to a tuberculosis model ngiven by a system of ordinary differential equations. nOptimal control strategies are proposed to minimize nthe cost of interventions. Numerical simulations nare given using data from Angola.

A TB-HIV/AIDS coinfection model and optimal control treatment

We propose a population model for TB-HIV/AIDS coinfection transmission dynamics, nwhich considers antiretroviral therapy for HIV infection and treatments for latent nand active tuberculosis. The HIV-only and TB-only sub-models are analyzed separately, nas well as the TB-HIV/AIDS full model. The respective basic reproduction numbers are computed, nequilibria and stability are studied. Optimal control theory is applied to the TB-HIV/AIDS model nand optimal treatment strategies for co-infected individuals with HIV and TB are derived. nNumerical simulations to the optimal control problem show that non intuitive measures ncan lead to the reduction of the number of individuals with active TB and AIDS.

Cost-Effectiveness Analysis of Optimal Control Measures for Tuberculosis

We propose and analyze an optimal control problem where the control system is a mathematical model for tuberculosis that considers reinfection. The control functions represent the fraction of early latent and persistent latent individuals that are treated. Our aim was to study how these control measures should be implemented, for a certain time period, in order to reduce the number of active infected individuals, while minimizing the interventions implementation costs. The optimal intervention is compared along different epidemiological scenarios, by varying the transmission coefficient. The impact of variation of the risk of reinfection, as a result of acquired immunity to a previous infection for treated individuals on the optimal controls and associated solutions, is analyzed. A cost-effectiveness analysis is done, to compare the application of each one of the control measures, separately or in combination.

Optimal control of a tuberculosis model with state and control delays.

We introduce delays in a tuberculosis (TB) model, representing the time delay on the diagnosis and commencement of treatment of individuals with active TB infection. The stability of the disease free and endemic equilibriums is investigated for any time delay. Corresponding optimal control problems, with time delays in both state and control variables, are formulated and studied. Although it is well-known that there is a delay between two to eight weeks between TB infection and reaction of bodys immune system to tuberculin, delays for the active infected to be detected and treated, and delays on the treatment of persistent latent individuals due to clinical and patient reasons, which clearly justifies the introduction of time delays on state and control measures, our work seems to be the first to consider such time-delays for TB and apply time-delay optimal control to carry out the optimality analysis.

Multiobjective approach to optimal control for a tuberculosis model

Mathematical modelling can help to explain the nature and dynamics of infection transmissions, as well as support a policy for implementing those strategies that are most likely to bring public health and economic benefits. The paper addresses the application of optimal control strategies in a tuberculosis model. The model consists of a system of ordinary differential equations, which considers reinfection and post-exposure interventions. We propose a multiobjective optimization approach to find optimal control strategies for the minimization of active infectious and persistent latent individuals, as well as the cost associated to the implementation of the control strategies. Optimal control strategies are investigated for different values of the model parameters. The obtained numerical results cover a whole range of the optimal control strategies, providing valuable information about the tuberculosis dynamics and showing the usefulness of the proposed approach.

Stability and optimal control of a delayed HIV model

We propose and investigate a delayed model that studies the relationship between HIV and the immune system during the natural course of infection and in the context of antiviral treatment regimes. Sufficient criteria for local asymptotic stability of the infected and viral free equilibria are given. An optimal control problem with time delays both in state variables (incubation delay) and control (pharmacological delay) is then formulated and analyzed, where the objective consists to find the optimal treatment strategy that maximizes the number of uninfected

An Optimal Control Approach to Malaria Prevention via Insecticide-Treated Nets

CD4^{+}

A SICA compartmental model in epidemiology with application to HIV/AIDS in Cape Verde

T cells as well as CTL immune response cells, keeping the drug therapy as low as possible.

An epidemic model for cholera with optimal control treatment

Malaria is a life threatening disease, entirely preventable and treatable, provided that the currently recommended interventions are properly implemented. These interventions include vector control through the use of insecticide-treated nets (ITNs). However, ITN possession is not necessarily translated into use. Human behavior change interventions, including information, education, communication (IEC) campaigns and postdistribution hang-up campaigns, are strongly recommended. In this paper, we consider a recent mathematical model for the effects of ITNs on the transmission dynamics of malaria infection, which takes into account the human behavior. We introduce in this model a supervision control, representing IEC campaigns for improving the ITN usage. We propose and solve an optimal control problem where the aim is to minimize the number of infected humans while keeping the cost as low as possible. Numerical results are provided, which show the effectiveness of the optimal control interventions.