Mathematically modeling the transmission and control of extensively drug resistan

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DESCRIPTION (provided by applicant): Extensively drug-resistant (XDR) tuberculosis has emerged as a significant international public health threat. Little is known about the transmission dynamics of XDR tuberculosis. The optimal set of interventions to prevent the further spread of XDR tuberculosis also remains controversial. The proposed project will offer insights into the transmission and control of XDR tuberculosis, using mathematical modeling techniques designed to achieve three research objectives: 1. To characterize the dynamics of XDR tuberculosis transmission using back-calculation techniques applied to data from Tugela Ferry, South Africa, where the largest cluster of XDR tuberculosis cases to date has been reported; 2. To apply these calculations to projections of the geographical spread of XDR tuberculosis; and 3. To use the resulting epidemic model to simulate the potential impact of hospital-based and community-level interventions to prevent the development and transmission of XDR tuberculosis. This research proposal provides detailed descriptions of the datasets and novel modeling techniques that will be used to achieve these research objectives. Relevance The emergence of extensively drug-resistant (XDR) tuberculosis is of major public health concern. Because this form of TB is nearly untreatable, it is of vital importance to determine where it will spread and how to best reduce its transmission. The goal of this project is to determine how to reduce XDR tuberculosis incidence, using mathematical models of its transmission.