Title: Structural racism, embodied histories, and health inequities: COVID-19, cancer, and the two-edged sword of data.
Abstract: In this presentation, I highlight key data – and data science – challenges for research on structural racism, embodied histories, and health inequities, focusing on COVID-19 and cancer. This requires grappling with what the science of racism and health entails: theoretically, methodologically, and in relation to the two-edged sword of racial/ethnic data and contrasts between studying racism vs “race” as causal drivers of population distributions of health. Guided by the ecosocial theory of disease distribution, which I have been developing since 1994, I present results of diverse studies I have led on US COVID-19 health inequities as well as critique the extant data. I then discuss several examples of my empirical research on cancer, Jim Crow, and both past and present residential segregation, analyzed in relation to both the Index of Concentration at the Extremes I have developed for racialized economic segregation and historical redlining (as delineated by the 1930s federally-sponsored maps produced by the Home Owners Loan Corporation (HOLC)). I conclude with reflections on counting for accountability, embodied histories, and the need for research on structural injustice and the people’s health to inform the work for health equity. See attached file for suggested readings.
This event is a part of our Bias^2 Series