Focusing on practical applications, this book introduces R, encompassing both Base R and the tidyverse, specifically for tackling operational research challenges in public health, infectious diseases, and energy generation. It aims to equip readers with the skills to derive actionable insights that enhance decision-making processes in these critical areas.
This interdisciplinary work presents system dynamics as a powerful tool for building simulation models of social systems to enhance decision-making. Grounded in the feedback perspective of complex systems, it offers a practical introduction, covering key concepts such as stocks, flows, and feedback. The application of computer simulation can address societal challenges like predicting the impact of emerging infectious diseases, estimating population growth, and assessing health services' capacity to cope with demographic changes. The text explains essential components of the system dynamics approach, including material delays, stock management heuristics, and modeling interactions between systemic elements. It features models from epidemiology, health systems, and economics to illustrate important concepts, utilizing the R programming language for an open-source and interoperable modeling experience. Additionally, the book describes hands-on techniques to enhance client confidence in system dynamics models, such as model testing, analysis, and calibration. Developed from the author's course, it is aimed at undergraduate and postgraduate students in management, operations research, computer science, and applied mathematics. Its focus on fundamental building blocks and the choice of R as a modeling language make it a valuable reference for integrating system dynamics with data analytic methods.