What is epidemiology? Changing definitions of epidemiology 1978-2017

CONTEXT

Epidemiology is a discipline which has evolved with the changes taking place in society and the emergence of new diseases and new discipline related to epidemiology. With these evolutions, it is important to understand epidemiology and to analyse the evolution of content of definitions of epidemiology.

OBJECTIVES

The main objective of this paper was to identify new definitions of epidemiology available since 1978. Secondary objectives were to analyse the content of these definitions, to compare them with those used by Lilienfeld and to determine whether changes have taken place over the last forty years.

METHODS

A review of grey literature and published literature was conducted to find the definitions of epidemiology written between 1978 and 2017.

RESULTS

102 definitions of epidemiology were retained. They helped to highlight 20 terms and concepts related to epidemiology. Most of them were already used in the definitions used by Lilienfeld. Five terms were present in more than 50% of definitions from the period 1978 to 2017: "population", "study", "disease", "health" and "distribution". Several developments have occurred: strengthening of the terms "control" and "health" already used, the concept of "disease" was less frequently encountered whereas the concepts "infectious diseases", "mass phenomenon" are no longer used in definitions from 1978 to 2017.

CONCLUSION

This evolution of content of definition of epidemiology is absent from books on epidemiology. A thematic analysis of definitions of epidemiology could be conducted in order to improve our understanding of changes observed.

Emerging Role of Epidemiologic Literacy

Background:

The ability to understand and apply epidemiology methods is a growing part of pharmacy practice, pharmacy accreditation standards, and evidence-based practice.

Objective:

TO examine the trends in epidemiology-related terminology used in the literature over the past 20 years.

Methods:

The frequency of the use of epidemiology-related terminology in 3 representative pharmacy Journals, 2 representative medical journals, and 1 public health journal from January through December 1984, 1994, and 2004 was recorded. The 3 pharmacy journals were the American Journal of Health-System Pharmacy (formerly American Journal of Hospital Pharmacy), The Annals of Pharmacotherapy (formerly Drug Intelligence and Clinical Pharmacy), and Pharmacotherapy. The 2 medical journals were the New England Journal of Medicine and The Journal of the American Medical Association (JAMA), and the public health journal was the American Journal of Public Health. The number of times an epidemiology-related term was used was summed for each year and each journal.

Results:

For all the journals examined in this study combined, the proportion of epidemiologic terms used in the literature has increased over the past 20 years. In 1984, of the total articles published in the 6 journals, 7.02% contained epidemiologic terms increasing to 12.27% and 15.46% in 1994 and 2004, respectively. The most dramatic differences in the 20-year comparisons were noted for Pharmacotherapy (0 to 17.75%) and JAMA (7.32 to 26.72%).

Conclusions:

The increase in the use of epidemiology-related terms has implications for both curricular planning in schools and colleges of pharmacy, as well as for continuing education programs and effective interprofessional communication.

The general epidemiologist: is there a place in today's epidemiology?

Epidemiology has changed remarkably during its growth in the past quarter century. One of those changes has been the ever-increasing specialization among its practitioners. In this commentary, the author explores the degree to which this phenomenon has shaped the field. A partial explanation for this trend is found in the decline in the availability of training funds not focused on specific disease areas. Although it appears likely that epidemiology can continue to flourish without general epidemiologists, the field will lose some of its ability to quickly respond to emerging public health challenges. The author considers steps necessary for the training and inclusion of general epidemiologists.

Biologic synergism and parallelism

In epidemiologic studies of two binary exposure factors, much attention has been given to the concept of synergism of the factors. The leading dictionary of epidemiology offers two definitions of synergism, one of which this author labels statistical and the other biologic. The epidemiologic literature has been largely concerned with statistical synergism, which is typically measured using additive or multiplicative interaction. This paper focuses on biologic synergism, on the related concept of biologic parallelism, and on the question of how much information can be gleaned about population amounts of biologic synergism and parallelism--information which is of vital interest to epidemiologists. A fundamental identity equates the difference between the amounts of biologic synergism and parallelism to the additive interaction. Two biologic models, the multistage model and the no-hit or immunity model, enhance the interpretation of multiplicative interaction as a measure of statistical synergism, but it is pointed out here that, unfortunately, both models incorporate the strong assumption that there is no parallelism. A third model, the single-hit or vulnerability model, makes the even stronger assumption that there is no biologic synergism and consequently that the additive interaction is equal to minus the amount of parallelism. A consequence of this fact is that a link which has been perceived in the literature to exist between the single-hit model and the additive interaction is false.

Taxonomic axes of epidemiologic study designs: a refutationist perspective

Overlap among the axes of study design used for classifying epidemiologic research creates a taxonomic problem, the complexity of which may be illustrated by Venn diagrams. The diagrams also suggest a solution: to rank axes according to their bearing on study validity. This is consistent with the refutationist criterion for distinguishing strong from weak science--the potential to refute alternative explanations. In epidemiology, this means refuting confounding, reverse-causation bias, selection or allocation bias, and misclassification bias. Using susceptibility to bias as a criterion for ranking axes, a simple taxonomy emerges that is compatible with widespread usage of terminology.