Applied Infectious Disease Modeling in R

Understanding how infectious diseases spread is critical for making informed public health decisions. Mathematical modeling allows us to simulate outbreak scenarios, project transmission rates, and evaluate the potential impact of interventions. This text-based course guides you through the core concepts of epidemiological modeling using the R programming language. You will transition from understanding basic biological transmission parameters to writing clean, reproducible code that simulates real-world disease dynamics. What you will learn: Understand the fundamental mathematical concepts behind compartmental models like SIR and SEIR; Write clean R code to simulate disease transmission dynamics over time; Analyze real-world outbreak data using modern data manipulation packages; Estimate key epidemiological parameters, including the basic reproduction number; Visualize epidemic curves and simulation results using modern plotting libraries; Apply model outputs to evaluate the effectiveness of public health interventions. The course begins with foundational epidemiological definitions and the theory of compartmental models. You will then progress step-by-step through translating these mathematical equations into executable R code, culminating in practical scenarios where you interpret model behaviors under different intervention strategies. This course is designed for public health professionals, students, researchers, and aspiring data analysts who want a beginner-friendly introduction to disease modeling. A basic familiarity with R is helpful, but no prior experience with mathematical modeling is required. Start reading today to build your foundational skills in infectious disease modeling.