Epidemiology is recognized as the science of public health, evidence-based medicine, and comparative effectiveness research. Causal inference is the theoretical foundation underlying all of the above. No introduction to epidemiology is complete without extensive discussion of causal inference; what's missing is a textbook that takes such an approach. takes a causal approach to the foundations of traditional introductory epidemiology. Through an organizing principle of study designs, it teaches epidemiology through modern causal inference approaches, including potential outcomes, counterfactuals, and causal identification conditions. Coverage in this textbook includes: · Introduction to measures of prevalence and incidence (survival curves, risks, rates, odds) and measures of contrast (differences, ratios); the fundamentals of causal inference; and principles of diagnostic testing, screening, and surveillance · Description of three key study designs through the lens of causal inference: randomized trials, prospective observational cohort studies, and case-control studies · Discussion of internal validity (within a sample), external validity, and population impact: the foundations of an epidemiologic approach to implementation science For first-year graduate students and advanced undergraduates in epidemiology and public health fields more broadly, offers a rigorous foundation in epidemiologic methods and an introduction to methods and thinking in causal inference. This new textbook will serve as a foundation not just for further study of the field, but as a head start on where the field is going.