CSDE Research Areas:
- Demographic Measurements and Methods
- Environments and Populations
- Health of People and Populations
Aja Sutton is an alumna of the Department of Geography at the University of Washington. During the 2020-2021 and 2021-2022 academic years, she was a TADA-BSSR NIH T32 Fellowship in Data Science and Demography Trainee through the Center for Studies in Demography and Ecology and was mentored by Zack Almquist and Jon Wakefield. She is also the Managing Editor for the Population Dynamics Lab. Her work integrates computational social science, geography, human health data, and disease ecology. Her dissertation delineated aspects of the political ecology of the COVID-19 pandemic in the United States. It aimed to clarify the relationships between political actors, messaging, identity, and polarization; and to identify the roles these have had in driving the population-level response to COVID-19 and uptake of transmission interventions such as mask-wearing across space and time. She is interested in improving the ways public health practitioners and policymakers can understand and work with communities to better prepare for major health emergency response. Ultimately, her doctoral research goals were to provide a clearer context of how and why our new political ecologic landscapes inform public interactions with emergency public health advice and policy, and what can be done in amid a highly dynamic sociopolitical climate. Aja is also trained as an human osteoarchaeologist (bioarchaeologist) with a specialty in the study of ancient diseases and the life course in past populations; and as a historian focused on the social history of health, the human body, and the politics of leisure and physical display in Western Europe and settler North America. Currently, Aja is a Postdoctoral Scholar in the Human Evolutionary Ecology and Health Lab (Dr. James Holland Jones) in the Department of Earth System Science at the Stanford Doerr School of Sustainability, Stanford University. There, she will be helping to develop the next generation of epidemiologic modeling methods.