System dynamics in medical education: a tool for life.

A course in system dynamics has been included in the first year of our university's six-year medical curriculum. System Dynamics is a discipline that facilitates the modelling, simulation and analysis of a wide range of problems in terms of two fundamental concepts viz. rates and levels. Many topics encountered in the medical school curriculum, from biochemistry to sociology, can be understood in this way. The course was introduced following a curriculum review process in which it was concluded that knowledge of systems would serve to enhance problem-solving skills and clinical reasoning. The specific characteristics of system dynamics, the widespread use of digital computers, and the availability of suitable software made it possible to introduce the course at this level. The syllabus comprises a brief review of relevant mathematics followed by system dynamics topics taught in the context of examples, which are primarily but not exclusively medical. It is anticipated that this will introduce new thought processes to medical students, including holistic thinking and improved graphical visualisation skills.

Facilitating Understanding, Modeling and Simulation of Infectious Disease Epidemics in the Age of COVID-19.

Interest in the mathematical modeling of infectious diseases has increased due to the COVID-19 pandemic. However, many medical students do not have the required background in coding or mathematics to engage optimally in this approach. System dynamics is a methodology for implementing mathematical models as easy-to-understand stock-flow diagrams. Remarkably, creating stock-flow diagrams is the same process as creating the equivalent differential equations. Yet, its visual nature makes the process simple and intuitive. We demonstrate the simplicity of system dynamics by applying it to epidemic models including a model of COVID-19 mutation. We then discuss the ease with which far more complex models can be produced by implementing a model comprising eight differential equations of a Chikungunya epidemic from the literature. Finally, we discuss the learning environment in which the teaching of the epidemic modeling occurs. We advocate the widespread use of system dynamics to empower those who are engaged in infectious disease epidemiology, regardless of their mathematical background.