Mathematical Modeling in Population Health Research

There is a long history of using mathematical modeling to study and improve aspects of population health. This chapter provides a brief overview of the diversity of such applications to complex health-related outcomes, including biological modeling (highlighting applications in infectious disease and human physiology), statistical modeling, cost-effectiveness analysis, and operations research (highlighting applications in queueing systems, Bayesian decision-making, and constrained optimization). Motivating objectives, typical model structure, and analyses are briefly described for each. As computational power has increased, computer simulation is often used to model complex phenomena. This chapter reminds readers of the many examples in which mathematical equations are used to parsimoniously represent complex systems and to understand their behavior. When mathematical models are tractable, analysts can obtain closed-form equations characterizing steady-state system behavior and tipping conditions—which provide a powerful and often easy to use tool for decision makers.