As the cornerstone science of public health, evidence-based medicine, and comparative effectiveness research, a clear understanding of study designs is central to the study of epidemiology. Causal inference is increasingly being understood as the theoretical foundation underlying epidemiologic study designs and the science as a whole. This textbook takes a causal approach to traditional introductory epidemiology, through the organizing principle of study designs and the lens of modern causal inference approaches (potential outcomes, counterfactuals, identification conditions). The intended aud ... More

As the cornerstone science of public health, evidence-based medicine, and comparative effectiveness research, a clear understanding of study designs is central to the study of epidemiology. Causal inference is increasingly being understood as the theoretical foundation underlying epidemiologic study designs and the science as a whole. This textbook takes a causal approach to traditional introductory epidemiology, through the organizing principle of study designs and the lens of modern causal inference approaches (potential outcomes, counterfactuals, identification conditions). The intended audience is first-year graduate students and advanced undergraduates in epidemiology and allied fields more broadly. Section I introduces 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. Section II describes three key study designs through the lens of causal inference: randomized trials, prospective observational cohort studies, and case-control studies. For each, the author discusses logistics and conduct, advantages and disadvantages including biases, basic approaches to analysis, and briefly reviews several additional study designs. Section III extends material in previous sections, moving from concerns about internal validity (within a sample) to questions of external validity and population impact. This book provides new students with a rigorous foundation in epidemiologic methods and an introduction to methods and thinking in causal inference, serving as an excellent foundation for further study of the field.