Infectious Disease Modeling: Building the SIR Model

Modern public health relies on mathematical frameworks to predict and manage the spread of infectious diseases. This course provides a clear entry point into compartmental modeling, helping you grasp the core logic behind epidemic simulations through conceptual understanding and foundational mathematics. You will gain a solid foundation in epidemiology by learning how to structure populations into Susceptible, Infectious, and Recovered groups. Through detailed written explanations and logical exercises, you will develop the intuition needed to interpret model outputs and understand the critical factors that drive an outbreak. What you'll learn: - Understand the core principles of compartmental modeling in epidemiology - Define and distinguish between Susceptible, Infectious, and Recovered states - Interpret mathematical rates, durations, and proportions in disease spread - Calculate and analyze the basic reproduction number (R0) and its significance - Practice building deterministic models to simulate epidemic curves - Evaluate how public health interventions alter model parameters and outcomes The course begins with essential terminology and the conceptual history of modeling before guiding you through the step-by-step logic of an SIR model. You will explore how small changes in transmission or recovery rates can lead to vastly different outcomes in a population, providing you with a modern perspective on disease management. This course is designed for beginners interested in public health, data science, or applied mathematics, with no prior modeling experience required. Start your journey into the world of mathematical epidemiology today.