*Harvard PhD Program in Health Policy Alumnus & Faculty Member
Dissertation Title："Policy Modeling and Economic Evaluation of Tuberculosis Control"
Tuberculosis (TB), a curable disease, kills nearly 2 million people annually. Approximately 80% of these deaths occur in 23 “high-burden” countries. The past decade has seen a rapid increase in efforts to reduce tuberculosis incidence and mortality through an expansion of TB control programs with financial support from international donors and technical assistance from the World Health Organization (WHO). This focus on tuberculosis has generated a need for the economic evaluation of alternative interventions for tuberculosis control. In this dissertation, mathematical models of tuberculosis are developed and simulation is used to estimate the cost-effectiveness of interventions to control tuberculosis.
Chapter One assesses the cost-effectiveness of alternative strategies for treating multidrug-resistant TB in Peru. The use of individualized regimens of second-line anti-tuberculosis drugs among patients who have failed or defaulted from first-line treatment was found to be highly cost-effective when using per-capita GDP as a threshold cost per life-year gained.
Chapter Two describes a model of tuberculosis epidemic in which TB control is conceived to consist of four sequentially connected components: program coverage, suspect recruitment, diagnosis, and treatment. Available resources for TB control can be distributed across these components. With a goal of minimizing deaths (and, alternatively, minimizing TB cases), the optimal allocation of resources across components for a given budget was estimated. In general, the optimal allocation of resources favors downstream program components (e.g., treatment) over upstream components (e.g., suspect recruitment). Results were compared to the World Health Organization’s stated implementation goals for TB control programs. Conventional tuberculosis control programs using the World Health Organization’s “DOTS” framework have not been sufficient for containing TB in high HIV-burden settings.
In Chapter Three, a mathematical model of interacting epidemics of TB and HIV was developed in order to quantify the potential health gain from and cost of augmenting conventional TB control in South Africa. The model was calibrated to match epidemiological data from South Africa. Policy alternatives included specific approaches to improving case detection, diagnostic testing, and treatment, including those that target HIV-infected persons. Our analysis demonstrates that several feasible and efficient TB control strategies exist that are incrementally more intensive than current policy in South Africa. These strategies, if implemented, can be expected to contain drug-resistance and accelerate the decline in TB incidence and mortality that will occur under the status quo strategy, at costs that appear reasonable for a middle income country. These analyses together indicate that cost-effective interventions for TB control exist in low-to-middle income settings with high TB burden, even in the presence of high levels of anti-tuberculosis drug-resistance or HIV coinfection.