Harnessing large-scale non-medical data to address public health problems in food systems and nutrition
Visiting speaker
Abigail Horn
Viterbi School of Engineering, University of Southern California
Past Talk
Hybrid
Thursday
Oct 10, 2024
Watch video
1:00 pm
EST
Virtual
177 Huntington Ave.
11th floor
Devon House
58 St Katharine's Way
London E1W 1LP, UK
Online
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Poor diet is the leading risk factor for cardio-metabolic diseases globally, responsible for 1 in 5 deaths annually—surpassing high blood pressure and tobacco. Despite advances like GLP-1 drugs, these diseases are steadily rising with 40% of Americans projected to have pre-diabetes by 2030. The burden is even greater in low-income and minority populations, where disease rates are increasing at a faster pace. The major failure of past approaches to improving public nutrition has been the almost exclusive focus on interventions to change individual knowledge, beliefs, and habits around healthy eating. Increasing evidence shows that food choices are shaped by system-level factors outside individual control. The availability of feature-rich digital trace data from sources beyond diet and health provides new opportunities for monitoring, measuring, and modeling food systems and dietary influences, and how individuals interact with these systems. In this talk, I will present studies that leverage non-medical data together with approaches from computational social science, systems modeling, and AI/ML to gain insights into how these systems affect food choices and nutritional disparities, shedding new light on potential intervention points in food systems. Topics covered include using logistics and trade data to model foodborne contamination and characterize supply-side drivers of food access, human mobility data to examine spatial drivers of eating behaviors, and restaurant menu and transaction data to assess food quality and access. These insights inform interventions to increase equitable access to healthy diets, in collaboration with partners in policy.
About the speaker
About the speaker
Dr. Abigail Horn is a Research Computer Scientist at the Information Sciences Institute and incoming Research Assistant Professor in the Daniel J. Epstein Dept. of Industrial and Systems Engineering in the School of Engineering at the University of Southern California. She was recently a Research Associate in the Dept. of Population and Public Health Sciences, also at USC. The general area of Abigail's research is the combination of approaches from network and computational social science and systems modeling with large-scale novel data sources to design solutions to pressing public health challenges. She focuses on problems in food systems and nutrition, and infectious disease modeling.
Dr. Abigail Horn is a Research Computer Scientist at the Information Sciences Institute and incoming Research Assistant Professor in the Daniel J. Epstein Dept. of Industrial and Systems Engineering in the School of Engineering at the University of Southern California. She was recently a Research Associate in the Dept. of Population and Public Health Sciences, also at USC. The general area of Abigail's research is the combination of approaches from network and computational social science and systems modeling with large-scale novel data sources to design solutions to pressing public health challenges. She focuses on problems in food systems and nutrition, and infectious disease modeling.