October 21, 2020
The COVID-19 pandemic has exposed existing health inequities for communities of color in the United States. Racism is a known structural cause of these health inequities. Counterfactuals are essential to our understanding of causal relationships in epidemiology, but how do you formulate a counterfactual for racism? This talk will explore the basis for counterfactual thinking in epidemiology and the ways in which we need to "reimagine" counterfactuals to address society's longstanding racism issues.
Nadia N. Abuelezam ’09 (mathematical biology) is an epidemiologist and assistant professor at the Connell School of Nursing. Abuelezam was trained in infectious disease epidemiology at the Harvard T.H. Chan School of Public Health. She has expertise in mathematical modeling and data analytic approaches in public health and in mitigating health inequities for vulnerable populations. Her current research focuses on understanding health risks in hard-to-reach populations, including immigrants. The goals of her program of research are to use quantitative methods and novel data streams to better understand inequities in health outcomes and healthcare access in resource-poor settings and vulnerable populations.
The Michael E. Moody Lecture Series illuminates the joy, wonder and applicability of mathematics. The Department of Mathematics established this series to honor Michael Moody, colleague, chair and honorary Harvey Mudd alumnus, whose vision and leadership guided the department to national prominence.
Zoom webinar information provided upon registration.