2 Author Bios

Nancy Krieger, PhD (she/her) (Principle Investigator for The Public Health Disparities Training Project 2.0) is Professor of Social Epidemiology and American Cancer Society Clinical Research Professor, in the Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health (HSPH), and also Director of the HSPH Interdisciplinary Concentration on Women, Gender, and Health. She is an internationally recognized social epidemiologist (PhD, Epidemiology, UC Berkeley, 1989), with a background in biochemistry, philosophy of science, and history of public health, plus 35+ years of activism involving social justice, science, and health. Dr. Krieger’s work addresses: (1) conceptual frameworks to understand, analyze, and improve the people’s health, including her ecosocial theory of disease distribution focused on embodiment and equity; (2) etiologic research on societal determinants of population health and health inequities, including structural racism and other types of adverse discrimination; and (3) methodologic research to improve monitoring of health inequities. She launched the initial Public Health Disparities Geocoding Project in the late 1990s to improve monitoring, analysis and action on the entangled impacts of social class and racism on population health and health inequities.

Jarvis Chen (he/him) is a social epidemiologist and Lecturer in Social and Behavioral Sciences at the Harvard T.H. Chan School of Public Health. His research focuses on methods for analyzing and understanding social inequities in health, particularly in relation to structural racism and socioeconomic deprivation. As a methodologist, Dr. Chen’s interests include development of methods for geospatial and spatiotemporal analysis, disease mapping, and causal inference in social epidemiology. Dr. Chen is also Associate Director of the PhD in Population Health Sciences Program in Harvard University’s Graduate School of Arts and Sciences and teaches several quantitative research methods courses at the school.

Enjoli Hall (she/her/hers) is a PhD student in the Department of Urban Studies and Planning at the Massachusetts Institute of Technology (MIT). Her work focuses on building infrastructures of collective care and action to understand and intervene in political and economic determinants of health.

Dena Javadi (she/her) is a PhD student in Population Health Sciences in the Department of Social and Behavioral Sciences at the Harvard T.H. Chan School of Public Health. Her prior work has been in Health Policy and Systems Research, with a focus on intersectoral action for health. Currently, her research explores the structural determinants of work-related health and wellbeing.

Justin Morgan (he/him) is currently pursuing a Ph.D. in Population Health Sciences in the Social and Behavioral Sciences department. His research interests center on power and the political determinants of health, with a focus on the practition of community engaged research to assess and address health equity.

Tamara Rushovich (she/her) is s a current PhD candidate in Population Health Sciences. Her research focuses on the ways that social factors and societal structures shape health. Prior to starting her PhD, Tamara worked in social services in Washington, DC and as an epidemiologist at the Chicago Department of Public Health. She has a BA in Sociology and an MPH in Epidemiology from the University of Michigan.

Sudipta Saha (he/him) is a Population Health Sciences PhD student in the Department of Social and Behavioral Sciences at Harvard University. His current research interests are at the intersection of social epidemiologic theories and infectious disease models. He is particularly interested in treating racial capitalism as a fundamental cause of health inequities to understand/illustrate how broader political-economic forces shape such inequities. He has a BSc in Microbiology from the University of Toronto, and a Master of Science in Global Health and Population at Harvard T.H. Chan School of Public Health.

Christian Testa (he/him) is a statistical analyst and programmer focused on modeling health outcomes and characterizing health inequities. His ongoing work is focused on COVID-19, epigenetic aging, survey data collection and analysis, discrimination, and area based social metrics. Christian is particularly interested in the application of flexible machine learning approaches in causal inference as well as the use of data visualization for the effective communication of scientific findings and their associated uncertainty.