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This talk will review common sources of bias in analyses of observational tuberculosis treatment cohorts and describe strategies, such as target trial emulation, for mitigating these biases, with the overall goal of improving the quality of evidence informing treatment. Illustrative examples will be provided. 

Speaker 

is an epidemiologist and Associate Professor in Global Health and Social Medicine at Harvard Medical School. The overarching goal of her work is to address critical knowledge gaps related to interventions for those most in need.  Her past work has included the design of studies to assess the effectiveness of cholera interventions, including vaccination; evaluation of community-based programs for care and treatment of HIV; and identification of optimal regimens for drug-resistant tuberculosis. She currently holds funding from the U.S. National Institutes of Health to adapt and apply epidemiologic methods commonly used in other fields to prospective tuberculosis treatment data, with the goal of improving the rigour of evidence and, thereby, patient care. 

Please note that you can join this event in person or you can join the webinar via Zoom.