Modeling Public Health and Healthcare Systems
This book aims to empower readers to learn and apply engineering, operations research, and modeling techniques to improve public health programs and healthcare systems. Readers will engage in in-depth study of disease detection and control strategies from a “systems science” perspective, which involves the use of common engineering, operations research, and mathematical modeling techniques such as optimization, queuing theory, Markov and Kermack-McKendrick models, and microsimulation. Chapters focus on applying these techniques to classical public health dilemmas such as how to optimize screening programs, reduce waiting times for healthcare services, solve resource allocation problems, and compare macroscale disease control strategies that cannot be easily evaluated through standard public health methods such as randomized trials or cohort studies. The book is organized around solving real-world problems, typically derived from actual experiences by staff at nongovernmental organizations, departments of public health, and international health agencies. In addition to teaching the theory behind modeling methods, the book aims to confer practical skills to readers through practice in model implementation using the statistical software R.