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Global Obesity Prevention Center

Education and Training


It's not enough for our own faculty and affiliates to adopt a systems-oriented approach to fighting obesity.  We need to ensure that professionals around the globe at all career stages are prepared to tackle obesity using a systems science approach.   

By educating and training professionals at all levels, the Global Obesity Prevention Center (GOPC) hopes to increase the number of public health researchers applying systems science theories and methods to the obesity epidemic



ETP 2.1We provide trainees from around the world with a range of opportunities designed to motivate them as systems thinkers and researchers, and to give them opportunities to apply their skills at preventing and finding solutions for obesity.

ETPOur trainees receive a combination of formal, course-based learning along with hands-on training in a range of methods and theories—including modeling and simulation techniques—pertinent to systems science and obesity. Students and trainees can also learn about applying systems science to obesity research through a range of activities, including our:



1. System Dynamics for Health Sciences

Instructors: Tak Igusa, David Rubin and Robyn Letts

Description: This introductory online course will teach you the fundamental principles of system dynamics as you learn how to use system dynamics software to explore problems relevant to your field of health. Whether you work in molecular biology, clinical medicine, health policy, or any other health-related field, this course will equip you to investigate the effects of time delays, feedback and system structure. 

Objectives/ Topics:


2. Systems Science and Obesity

Instructors: Jessica Jones-Smith, Dan Taber, Thomas Glass, Kayla de la Haye and Rahmatollah Beheshti

Description: This online course 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.

 Objectives/ Topics: 


  1. Complex Systems and Obesity in Human Populations

  2. Epidemiology of Diabetes and Obesity

  3. Introduction to Health Systems Modeling

  4. Systems Science in Public Health: Basic Modeling and Simulation Methods



We recruit post-doctoral and pre-doctoral fellows with support from collaborating faculty, both at the Johns Hopkins University and from outside institutions. Fellows pursue professional development opportunities at the Bloomberg School for a one-year period. A dual mentorship team is assigned based on research interests. Fellows work with these mentors to identify specific research and academic interests and cultivate desired skill sets. We seek applicants who can work with one or more of the ongoing projects in the Center and who bring additional systems science skills and modeling experience. Trainees also have full access to course offerings both at the Bloomberg School and the Johns Hopkins Whiting School of Engineering.



Each year, the Global Obesity Prevention Center welcomes a select number of visiting scholars to spend a month at Johns Hopkins University, where they can train and participate in relevant research projects. The experience offers hands-on experience and first-hand knowledge of how systems science research is integrated to public health and obesity. We offer financial assistance to cover travel and living costs. Visiting scholars may seek additional support from their home institutions and their University sponsoring mentors if they wish to extend their stay.

Additional Information

Education and Training Overview
Please email for further information.