This issue of the journal includes 3 commentaries1–3 on education in epidemiology, based on a symposium organized by the Editors of Epidemiology for the 2007 meeting of the Society for Epidemiologic Research (SER). The rapid changes in epidemiologic research and practice pose a serious challenge for training epidemiologists, as demonstrated by the large turnout and lively discussion at the SER meeting. The topics covered in these 3 commentaries reflect some of the most pressing changes and their associated challenges: the rise of molecular epidemiology, the ongoing need to redefine core epidemiologic methods and to develop optimum didactic approaches, and the increasing difficulty of assuring competency in primary data collection. In addressing these topics, the authors have drawn on the limited literature on education in epidemiology (in particular, a volume developed by the International Epidemiological Association4), and on personal experiences at their home institutions.
Perera and Herbstman1 address molecular epidemiology, an interdisciplinary research approach increasingly available through technological advances, particularly in genetics and genomics. They use the example of DNA adducts resulting from exposure to polycylic aromatic hydrocarbons to illustrate the depth and breadth of knowledge needed for molecular epidemiology research. They offer the analogy of epidemiologist as “orchestra conductor,” who needs to understand and coordinate the unique contributions of each instrument (or contributing discipline). A molecular epidemiologist needs to be well grounded in epidemiologic methods, the biology of the problem under study, and the details of the measurements made in the laboratory.
How can training programs develop the needed competencies? While Perera and Herbstman do not address this question directly, the answer clearly lies in interdisciplinary training that mirrors the scope of research in molecular epidemiology. Given the range of epidemiologic inquiry (which increasingly includes molecular components), some familiarity with the laboratory is needed by all trainees; specialized intensive training, tailored for individual students, must be offered as well. Cross-disciplinary training in molecular epidemiology is offered by some schools, but far from all.
It is remarkable that, even a half century after the emergence of epidemiology as a formal academic discipline, there is still no consensus on the core methods that should be taught in epidemiology graduate programs. Perhaps this is because the methods themselves are continuously evolving. Course requirements vary widely across the many new programs in epidemiology and public health. At the more established schools, courses tend to reflect their historical origins and the approaches taken by strong methodologic teachers.
Gange2 provides a thoughtful perspective on the teaching of epidemiologic methods, based in part on recent revisions to the core curriculum in epidemiology at the Johns Hopkins Bloomberg School of Public Health. He highlights key issues: the heterogeneity of students, the often ill-coordinated overlap between courses in epidemiology and biostatistics, the need to foster skills in data analysis, and the lack of didactic resources. His commentary ends with recommendations for improving the teaching of epidemiologic methods, some of which could be readily implemented.
The ability to carry out all aspects of epidemiologic research—from data collection to analysis, interpretation, and reporting of findings—has long been considered a universal requirement for epidemiologists. As described by Buring,3 there was a time when doctoral thesis research began with writing a grant application and obtaining funding, and continued through all the phases of research, including hands-on data collection. The evolution of epidemiologic investigation towards larger, more expensive, and more technology-laden approaches has largely displaced this earlier model for dissertation research. Increasingly, students build thesis research on secondary data analysis, with some participating in additional data collection from ongoing studies.
Buring argues strongly for maintaining the development of skills in primary data collection within doctoral programs. Her arguments are persuasive. She proposes that ancillary studies, added to larger study platforms, can give students the needed experience in data collection. She offers the example of the more than 50 ancillary studies built upon the framework of the Women's Health Study. We add that doctoral programs should also consider courses and applied experiences to assure that students acquire competency in the conduct of epidemiologic research. Experience in secondary data analysis alone is not sufficient for graduate training; additional course work or other opportunities must be provided if the dissertation does not include primary data collection.
These 3 commentaries make clear that these are “a-changin’” times for educational programs in epidemiology. The challenges are substantial, ongoing, and incompletely met by even the best of graduate programs. To date, professional organizations have had a limited role in addressing these challenges: the International Epidemiological Association has published 2 editions of its compilation, the American College of Epidemiology convened a workshop on doctoral education, and the Association of Schools of Public Health has had a limited agenda on education in epidemiology. We are convinced by these commentaries and our own experience as department chairs that a more proactive and comprehensive approach is needed to improve graduate training in epidemiology. The basis for structuring training programs should be thoughtful and explicit, with ongoing efforts to compare programs and learn from successes and failures. Professional societies can provide a forum to draw out these issues and raise the critical questions on how to educate epidemiologists. Collective discussion and action would help to ensure that this generation of trainees is equipped to use the expanding base of knowledge and tools they will need to address emerging scientific and public health challenges.
1. Perera FP, Herbstman JB. Emerging technology in molecular epidemiology: what epidemiologists need to know. Epidemiology
2. Gange SJ. Teaching epidemiologic methods. Epidemiology
3. Buring JE. Primary data collection: what should well-trained epidemiology doctoral students be able to do? Epidemiology
4. Olsen J, Saracci R, Trichopoulos D, eds. Teaching Epidemiology
. A Guide for Teachers in Epidemiology, Public Health and Clinical Medicine
. 2nd ed. Oxford: Oxford University Press; 2001.