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.
Systems Science and Obesity
约翰霍普金斯大学课程信息
学生职业成果
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学生职业成果
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约翰霍普金斯大学
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教学大纲 - 您将从这门课程中学到什么
Module 1
Obesity, the facts of the case, and human populations through a systems science lens.
Module 2
Complex systems, system dynamic models, and developing a stock and flow. This module includes a lab lesson.
Module 3
Social networks and obesity, neighborhoods and noshing, and prices and poverty.
Module 4
Agent based modeling and conceptual motivation for agent based modeling. This module includes a lab lesson.
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来自SYSTEMS SCIENCE AND OBESITY的热门评论
Fantastic course. Really thought provoking, and well presented. Useful as an intro to systems thinking, and as a way to understand the obesity epidemic in a nuanced way.
This course was surprisingly challenging and educational. I had little background in system science, and very much enjoyed the learning process!
Tough to understand for someone from a non-math background. However basic concepts are easy to discern and learn in relation to obesity
Very interesting and useful tools for analyzing complex networks and designing interventions.
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