Tracing Tuberculosis Transmission

Leonid Chindelevitch

Abstract

This project focuses on modelling various aspects of the tuberculosis disease, the leading infectious disease killer in the world today. Starting from genomic data collected from multiple sources, we will attempt to extract enough information to develop an accurate model of tuberculosis mutation over time and the emergence of drug resistance, a phenomenon that leads to the bacterium evading the drugs targeting it. In addition, we will design an algorithm for converting between various types of molecular information so as to expand the range of past outbreaks that can be compared to one another. Lastly, using the model, we will analyze a dataset to distinguish between drug resistance acquired as a result of treatment from that transmitted from a previously resistant patient, a currently unsolved and policy-relevant problem. Project Description: Specific Aim 3: Infer the transmission dynamics of a pathogen from its phylogenetic treeThe successful execution of my research program will substantially advance the state-of-the-art capabilities of molecular epidemiology as a whole, by enabling it to give complete answers to challenging real-world questions about the transmission of infectious diseases. Potential applications include the use of genomic assays as real-time diagnostic tools based on the identification of complex infections, the evaluation of public health policy interventions in light of an understanding of the drivers of resistance in infectious diseases, and improved monitoring and case-finding based on a classification of transmission events as occurring in a hospital setting or in a community. In the long-term, all these efforts will contribute towards interrupting transmission of infectious diseases.