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DTSTART;TZID=UTC:20260609T120000
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SUMMARY:Combining Evidence from Observational Studies and Population Surveys to Better Predict Cardiovascular Disease Risk
DESCRIPTION:Cardiovascular diseases (CVD) remain the leading cause of death worldwide. Although CVD mortality declined substantially over the past five decades\, progress in the United States has slowed since 2010. Reviving these gains will require more effective implementation of prevention strategies\, including improved methods for identifying individuals at highest risk. \nIn this presentation\, Dr. Goodarz Danaei will discuss emerging approaches to cardiovascular risk prediction and prevention\, including the use of causal inference methods and nationally representative data to develop more accurate risk models. He will explore the limitations of existing prediction tools\, which often rely on outdated cohort studies or nonrepresentative electronic medical record data\, and present new research aimed at improving population-level prevention strategies in the United States and globally. \nThis webinar is free and open to the public and will include time for audience Q&A. \nRegister \n  \nSpeaker\n \nGoodarz Danaei\, MD\nBernard Lown Professor of Cardiovascular Health\, Global Health and Population\, Harvard T.H. Chan School of Public Health; Faculty Director\, Bernard Lown Scholars in Cardiovascular Health Program \nDr. Goodarz Danaei is the Bernard Lown Professor of Cardiovascular Health in the Department of Global Health and Population at the Harvard T.H. Chan School of Public Health. His global health research focuses on quantifying the population-level impact of risk factors and preventive interventions on cardiovascular disease globally\, with a focus on low- and middle-income countries. He led the team that developed the only country-level risk prediction model for cardiovascular disease (www.globorisk.org) that has since been used by dozens of researchers and clinical groups worldwide. His epidemiological research applies advanced methods of causal inference to emulate the design and analysis of target trials using electronic health records and other observational data. As a member of CAUSALab\, he has helped develop and apply marginal Structural Models and the G-formula to quantify causal effects of lifestyle changes or medications on long-term risk of cardiovascular diseases. \n  \nGlobal Health Research and Innovation Speaker Series\nThe Harvard Global Health Institute’s Global Health Research and Innovation Speaker Series showcases the latest scholarly and scientific advancements in global health across Harvard and beyond\, to make cutting-edge research accessible to a diverse global audience\, and to spark innovative solutions in the pursuit of health equity and improved health outcomes worldwide. The public series takes place virtually on the second Tuesday of each month from 12:00 to 12:45 pm ET. Each session will include a presentation by a featured speaker showcasing their innovative research in global health\, followed by a moderated Q&A. \nThe Harvard Global Health Institute provides a platform for different perspectives and debates within the field of global health through a variety of media. The views expressed in these events and programs are solely those of the speakers\, authors\, researchers\, and participating audience. As such\, they do not speak for the institute or the university.
URL:https://globalhealth.harvard.edu/event/research-innovation-goodarz-danaei/
LOCATION:Zoom\, Virtual: Zoom
CATEGORIES:Virtual
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