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Epidemiology is the study of health and disease in a population. Studying the causes, distribution, risk factors, and treatment of diseases, all of which fall under its scope, provides the cornerstone for research into explaining how and why infectious diseases occur. This chapter is designed to provide a brief introduction to the core principles of clinical research and epidemiology. Our goal is to present clinicians with an overview of the key terms and concepts found throughout published research, and we hope that this chapter will serve as a useful reference for pediatricians seeking to better understand the fundamentals of infectious diseases epidemiology.
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In this chapter, we begin with a discussion of study designs, including the strengths and weaknesses of different types of studies. We then explore important concepts used in studies of diagnostic tests: sensitivity, specificity, positive and negative predictive values, and likelihood ratios. Next, we discuss statistical analysis by comparing univariate and multivariate analyses, while explaining terms used to define the magnitude of an effect such as odds ratios (ORs), relative risk (RR), and confidence intervals. Finally, we end the chapter with an examination of relative risk reduction (RRR), absolute risk reduction (ARR), and number needed to treat—measures used to enumerate the benefits of an intervention. We hope that the information presented in this chapter provides a concise overview of the key concepts of epidemiologic and clinical research in infectious diseases.
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A variety of study designs are utilized in clinical research and each allows authors to address different questions. Depending on whether an author would like to determine the prevalence of a disease, the natural course of an infection, or the effectiveness of a treatment, for example, will determine which study design the investigator will use. In general, studies can be broken down into two principle types: descriptive and analytic. Descriptive studies include case reports, case series, and survey studies, all of which are used primarily to generate hypotheses.1–4 As the name implies, these types of study designs allow authors to describe the characteristics of a single patient or group of patients with a common disease. However, since these studies do not use a control or comparison group, they are poorly suited to make causal inferences. Instead, they are more useful for characterizing emerging or rare diseases, such as avian influenza A, where little is known about the natural course of disease.
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Analytic studies are hypothesis-testing in nature and are better equipped to explore the relationship between cause and effect. Analytic studies can be further subdivided into observational and experimental studies. Observational studies include cross-sectional, case-control, and cohort studies, and provide information about prevalence, incidence, causes, risk factors, and outcomes of disease. Experimental studies test the effects of an intervention and include clinical trials, both randomized and nonrandomized. Randomized clinical trials (RCTs) are often considered the most powerful and scientific study designs, and are the gold standard for evaluating the efficacy of therapies and ...