About this course: Systems science has been instrumental in breaking new scientific ground in diverse fields such as meteorology, engineering and decision analysis. However, it is just beginning to impact public health. This seminar is designed to introduce students to basic tools of theory building and data analysis in systems science and to apply those tools to better understand the obesity epidemic in human populations. There will also be a lab in which students will use a simple demonstration model of food acquisition behavior using agent-based modeling on standard (free) software (netlogo). The central organizing idea of the course is to examine the obesity epidemic at a population level as an emergent properties of complex, nested systems, with attention to feedback processes, multilevel interactions, and the phenomenon of emergence. While the emphasis will be on obesity, the goal will be to explore ways in which the systems approach can be applied to other non-communicable diseases both nationally and internationally. Topics will include: a) the epidemiology of obesity across time and place, b) theories to explain population obesity, c) the role of environments and economic resources in obesity c) basic concepts and tools of systems science, d) modeling energy-balance related behaviors in context, e) agent-based models, systems dynamic models, and social network models
Taught by: Jessica Jones-Smith, Assistant Professor
Human Nutrition
Taught by: Rahmatollah Beheshti, Postdoctoral Fellow
Department of Civil Engineering
Taught by: Daniel Taber, Assistant Professor
School of Public Health (UT Health)
Taught by: Kayla de la Haye, Assistant Professor of Preventative Medicine
Keck School of Medicine (USC)
Taught by: Thomas Glass, Professor
Epidemiology
| Level | Beginner |
| Commitment | 4 weeks of study, 2-3 hours/week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
- Video: Welcome to the Course
- Video: Obesity, The Facts of the Case (Or Why Obesity Pushes Our Buttons) - Tom Glass
- Video: Beyond the Usual Suspect: Why This Case Is Hard To Crack
- Video: Explanations: The Food Supply, A System of Interest
- Video: Obesity in Human Populations Through a Systems Science Lens - Tom Glass
- Video: Taking a Systems Perspective: 5 Key Features
- Video: What is so "Systemy" About Obesity?
- Video: What Is a Complex System?
- Video: Nuts and Bolts of System Dynamics Models
- Video: Developing a Stock and Flow Model
- Video: Policy Resistance
- Video: Coding tutorial for systems dynamics model
- Video: From stock and flow diagram to developing a SD model in Vensim
- Reading: Important: Models for Lab Assessment
- Video: What Are Social Networks?
- Video: Social Network Analysis
- Video: Obesity & Social Networks
- Video: Neighborhoods and Noshing: Foraging and the Food Environment
- Video: Why Should We Care About Neighborhoods for a Systems Science of Obesity
- Video: Foraging Theory: A Unifying Framework?
- Video: Lecture 6: What's price (and income) got to do with it?
- Video: Less money, more problems?
- Video: Taxman: Can Price Manipulations Be Used to Promote Healthful Eating
- Video: Agent-based modeling: A simpler way to understand complexity
- Video: Why agent-based modeling?
- Video: Development of a Simple Model with Environment, Peer Networks, and Agent Behaviors
- Video: Food Foraging ABM:Embedded in a GIS-Based Environment
- Video: Lab 2 Part 1: Tutorial on building ABMs in Netlogo environment
- Video: Lab 2 Part 2: ABM for Food Store; Food Foraging ABM
- Video: Lab 2 Part 3: Income-Diet model example with extensions
- Reading: Important: Models For Lab Assessment 2
- Video: Congratulations!
- Reading: Learn more about the Global Obesity Prevention Center
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This course was surprisingly challenging and educational. I had little background in system science, and very much enjoyed the learning process!
amazing!
It is only that the language is little hard for non native speakers
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HH
Very interesting and useful tools for analyzing complex networks and designing interventions.