Systems Science & Obesity: Understanding Health Issues
Explore obesity through systems science. Learn tools for theory building & data analysis to tackle this complex public health challenge.
Explore obesity through systems science. Learn tools for theory building & data analysis to tackle this complex public health challenge.
Dive into the world of systems science and its application to public health, focusing on the obesity epidemic. This course introduces students to essential tools for theory building and data analysis in systems science, applying them to understand obesity in human populations. Through lectures and hands-on labs, you'll explore obesity as an emergent property of complex, nested systems, examining feedback processes, multilevel interactions, and the phenomenon of emergence. Covering topics from obesity epidemiology to agent-based modeling, this course equips you with a systems approach to tackle non-communicable diseases both nationally and internationally.
4.6
(199 ratings)
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English
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What you'll learn
Understand the epidemiology of obesity across time and place
Explore theories explaining population obesity
Learn basic concepts and tools of systems science
Apply systems thinking to complex public health issues
Develop skills in agent-based modeling and system dynamics
Analyze the role of environments and economic resources in obesity
Skills you'll gain
This course includes:
7.425 Hours PreRecorded video
6 assignments
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There are 4 modules in this course
This course introduces students to the application of systems science in understanding and addressing the obesity epidemic. It covers the epidemiology of obesity, theories explaining population obesity, and the role of environments and economic resources. Students will learn basic concepts and tools of systems science, including agent-based models, systems dynamic models, and social network models. The course emphasizes viewing obesity as an emergent property of complex, nested systems, with attention to feedback processes, multilevel interactions, and the phenomenon of emergence. Through lectures and hands-on labs, students will gain practical experience in modeling energy-balance related behaviors in context and applying systems approaches to non-communicable diseases.
Obesity, the facts of the case, and human populations through a systems science lens
Module 1 · 2 Hours to complete
Complex systems, system dynamic models, and developing a stock and flow
Module 2 · 2 Hours to complete
Social networks and obesity, neighborhoods and noshing, and prices and poverty
Module 3 · 2 Hours to complete
Agent based modeling and conceptual motivation for agent based modeling
Module 4 · 3 Hours to complete
Fee Structure
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Instructors
Former Assistant Professor at Johns Hopkins University
Jessica Jones-Smith is a public health expert who previously served as an Assistant Professor at the Johns Hopkins Bloomberg School of Public Health for four years. She specializes in the socioeconomic factors influencing food choices and health outcomes, particularly in relation to obesity and nutrition-related health disparities. Her career began in San Francisco as a dietitian, where she observed significant disparities in diet quality across different socioeconomic groups. After her tenure at Johns Hopkins, she joined the University of Washington as an Associate Professor, where she leads initiatives to address obesity and food-related health issues. Jones-Smith has been involved in various research projects, including studies on the impact of Seattle's soda tax on purchasing behaviors. She holds multiple degrees, including a PhD in Nutritional Epidemiology from the University of North Carolina–Chapel Hill and an MPH in Public Health Nutrition from the University of California–Berkeley. Her work emphasizes the importance of integrating health communication with policy to improve public health outcomes.
Postdoctoral Fellow
Rahmtaollah Beheshti is a postdoctoral fellow at Johns Hopkins University, where he collaborates with both the Bloomberg School of Public Health and the Whiting School of Engineering. He holds a PhD in computer science and an MSc in artificial intelligence. Dr. Beheshti has been involved in designing various public health-related models, particularly focusing on obesity, smoking, and population growth. Additionally, he has taught related courses on several occasions at Johns Hopkins University.
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4.6 course rating
199 ratings
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