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Epidemiology is the study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to control of health problems (Last 2001). Epidemiology is the scientific study of factors affecting the health and illness of individuals and populations, and, in this capacity, it serves as the foundation and logic of interventions made in the interest of the public’s health. The acting epidemiologist works on issues from the practical, such as outbreak investigation, environmental exposure, and health promotion, to the theoretical, including the development of statistical, mathematical, philosophical, and biological theory. To this end, epidemiologists employ a range of study designs from the observational to experimental with the purpose of revealing the unbiased relationships between exposures such as nutrition, HIV, stress, or chemicals to outcomes such as disease, wellness, and health indicators.
Epidemiological studies are generally categorized as descriptive, analytic (aiming to examine associations, commonly hypothesized causal relationships), and experimental (a term often equated with clinical or community trials of treatments and other interventions).
Epidemiologists work in a variety of settings. Some epidemiologists work "in the field", i.e., in the community, commonly in a public health service, and are at the forefront of investigating and combatting disease outbreaks.
Etymology
The etymology of "epidemiology" (Greek epi = upon, among; demos = people, district; logos = word, discourse) suggests that it applies only to human populations. But the term is widely used in studies of animal populations ("veterinary epidemiology"), although the term "epizoology" is available, and it has also been applied to studies of plant populations ("botanical epidemiology"); see Nutter 1999.
Epidemiology as causal inference
Although epidemiology is sometimes viewed as a collection of statistical tools used to elucidate the associations of exposures to health outcomes, a deeper understanding of this science is that of discovering causal relationships. This conceptualization of epidemiology is difficult to grasp because our internal notions of causation are often poorly developed, frequently being predicated on the notion of a one-to-one relationship. For example, almost everyone would agree that gravity causes a dropped ball to fall towards the ground, but would most agree that drinking one glass of milk a day will cause weight loss? Even very heavy smokers know that their vice causes lung cancer, but only 10% of life-long smokers will get lung cancer. How can this be?
The answer is complex and involves philosophical notions of causality, induction, deduction, logic and other dense topics. It is nearly impossible to say with perfect accuracy how even the most simple physical systems will behave, much less the complex field of epidemiology that draws on biology, sociology, mathematics, statistics, anthropology, psychology, and policy. However, for the epidemiologist the key is in the term inference. As epidemiologists, we use gathered data and a broad range of bio-medical and psycho-social theories in an iterative way to generate or expand theory, to test hypotheses,and to make educated, informed assertions about which relationships are causal and exactly how they are causal.
Epidemiology as advocacy
An alternative aspect of an epidemiologist’s duty is to advocacy for the health of populations, bearing in mind the outpost perspective they have over factors that affect a whole population. In this capacity the epidemiologist is not limited by the strict requirements for scientific accuracy. This of course does not mean that the epidemiologist can advocate for whatever position they please independent of the data, but presentation of the data be adjusted to help change behavior or understanding. For example, consider these two alternative admonishments against smoking:
1. Smoking has been consistently linked to health problems such as lung cancer and coronary heart disease in several large prospective studies, this link has been deemed causal by a complex process of induction, consensus, and modeling.
2. Smoking will kill you.
Although statement one is more accurate, statement two has an air of finality and explicit causation that may help to reduce the rate of smoking, albeit scientific and philosophically questionable.
The best epidemiologist as advocate will consider the broader intellectual landscape beyond the epidemiology and public health literature to render judgment on a course of action for a population, in this manner they are employing a different analytical framework than the Cartesian framework that is more common in scientific epidemiology. However, it is rare for one person to wield the skills and embody the features required to be a leader in both the scientific and advocacy aspects of epidemiology.
Measures
- Measures of occurrence
- Incidence measures
- Incidence density (also known as Incidence rate) (Szklo & Nieto, 2000)
- Hazard rate
- Cumulative incidence
- Prevalence measures
- Point prevalence
- Period prevalence
- Measures of association
- Relative measures
- Risk ratio
- Rate ratio
- Odds ratio
- Hazard ratio
- Absolute measures
- Risk/rate/incidence difference
- Attributable risk
- Attributable risk in exposed
- Percent attributable risk
- Levin’s attributable risk
History of epidemiology
Dr. John Snow is famous for the suppression of an 1854 outbreak of cholera in London's Soho district. He identified the cause of the outbreak as a public water pump on Broad Street and had the handle removed, thus ending the outbreak. (It has been questioned as to whether the epidemic was already in decline when Snow took action.) This has been perceived as a major event in the history of public health and can be regarded as the founding event of the science of epidemiology.
Other pioneers include Danish physician P. A. Schleisner, who in 1849 related his work on the prevention of the epidemic of tetanus neonatorum on the Vestmanna Islands in Iceland. Another important pioneer was Hungarian physician Ignaz Semmelweis, who in 1847 brough down infant mortality at Vienna hospital by instituting a disinfection procedure. His findings were published in 1850, but his work was ill received by this colleagues, who discontinued the procedure. Disinfection did not become widely practiced until British surgeon Joseph Lister "discovered" antiseptics in 1865 in light of the work of Louis Pasteur.
In the early 20th century, mathematical methods were introduced into epidemiology by Ronald Ross, Anderson Gray McKendrick and others.
Another breakthrough was the 1954 publication of the results of a British Doctors Study led by Richard Doll and Austin Bradford Hill, which lent very strong statistical support to the suspicion that tobacco smoking was linked to lung cancer.
References
- Last JM (2001). "A dictionary of epidemiology", 4th edn, Oxford: Oxford University Press.
- Nutter FW Jr (1999) "Understanding the Interrelationships Between Botanical, Human, and Veterinary Epidemiology: The Ys and Rs of It All. Ecosystem Health 5 (3): 131-140".
- Szklo MM & Nieto FJ (2002). "Epidemiology: beyond the basics", Aspen Publishers, Inc.
See also
External links
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