While the general approach to the measurement and analysis of infectious disease epidemiology is closely related to that used in the study of chronic diseases, several important differences exist. The first of these is transmissibility. As Johann Geisecke writes, "in infectious disease epidemiology a case is also a risk factor" for disease in other population members (Geisecke 2002). The corollary of transmissibility is immunity: disease-susceptible individuals provide the "fuel" necessary for epidemics to occur. Conversely, having sufficient immune individuals in a population can decrease the risk of infection for non-immune individuals too. These fundamental properties of communicable diseases can easily be represented, simulated, and evaluated using mathematical models of communicable diseases. Such models are not only a tool for understanding infectious processes but can also serve as a platform for comparison of the expected effectiveness and cost-effectiveness of communicable disease control strategies. This course will serve as a basic introduction to the mathematical model of infectious diseases. All course materials are rooted in, or derived from, current public health challenges.