Definition
Epidemiology has been defined as “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, 1988). It is basically the study of how diseases occur in populations and why.

Emergence of epidemiology

Though not called as “Epidemiology,” several studies and ideas resembling epidemiological work have been done over the centuries. Hippocrates, in his work “Airs, Waters, and Places” written 2400 years ago, linked disease with the environment. James Lind’s trial of fresh fruit against scurvy in 1747 could be the earliest example of a ‘clinical trial.’ William Farr working in the Office of the Registrar General in England in 1840s demonstrated the effect of imprisonment on mortality. John Snow’s work “On the Mode of Communication of Cholera” in 1855, is considered a classic in the field of epidemic investigation.

Modern epidemiology

In the 1950s a large number of studies were done on smoking and health. Landmark case control and cohort studies on smoking and lung cancer by Richard Doll & Bradford Hill in 1952 and 1954, established epidemiological methods on a strong footing. Indeed, they added credibility to the new discipline. The Framingham Heart Study was initiated in 1949. Large volumes of complex data collected during this study [the study is still going strong after 50 years!] and the emergence of computer technology lead to the evolution of complex statistical analysis techniques like multivariate analysis and modeling. The field trial of the Salk vaccine in 1957 was the world’s largest field trial. Thus, the epidemiology of today is still a young science; the ideas, however, are very old.

Basic tenets of epidemiology

Oriented towards groups rather than individuals: While clinical observations are made on individual patients, epidemiological observations are made on groups of people (populations). This is one reason why statistical methods are necessary for analysing epidemiological data.

Table 1: Cholera cases in Madras city, 1990 – 1996
Year Cholera cases in Madras city
1990 505
1991 600
1992 700
1993 800
1994 1000
1995 1200

All findings must relate to a defined population: It is not enough to merely enumerate those who have a certain disease; the population at risk of developing that disease also has to be enumerated. Only then can valid conclusions be drawn. For example, a casual look at Table 1. may convince a person that between 1990 and 1995, the cholera situation has worsened in Madras (fictitious data).When the same data is analysed after accounting for the population of the city during the same period (Table 2), it can be seen that the cholera incidence has hardly changed between 1990 and 1996.This example demonstrates the importance of not just looking at the numerator but also comparing it with a valid denominator. Epidemiologists have actually been defined as people in the search of the denominator!

Table 2: Annual incidence of cholera in Madras city, 1990- 96
Year Population of Madras Cholera cases Annual incidence
of cholera per 1000 population
1990 35,00,000 505 0.14
1991 43,00,000 600 0.13
1992 49,00,000 700 0.14
1993 53,00,000 800 0.15
1994 62,00,000 1000 0.16
1995 72,00,000 1200 0.16

Conclusions are based on comparisons: If everyone in the world smoked 20 cigarettes a day the association between smoking and lung cancer would have never been uncovered. Epidemiology thrives on heterogeneity. It is because there are variations in populations that epidemiological research is possible.Comparing the rates of disease frequency among the exposed and the unexposed is therefore a classic epidemiological method. Fig 1. illustrates the association between death rates from lung cancer (annual death rate per 1000) and number of cigarettes smoked (Doll & Hill 1964). It can be seen that the rate of death increased almost linearly with the number of cigarettes smoked. Description of events by time, place and person: The occurrence of an event (say a certain disease) is usually described in terms of when it occurred, where it occurred and who were affected. Such a description helps in understanding the disease and also in formulating a hypothesis about its causation.

The epidemiological sequence

Whenever a new condition occurs, the following epidemiological sequence is usually started (Tyler CW, Last JM 1992). This sequence involves:

1.Observation
2.Counting of cases or events
3.Relating cases or events to the population at risk
4.Relating specific events to specific factors
5.Making comparisons
6.Developing the hypothesis
7.Testing the hypothesis
8.Making scientific inferences
9.Conducting experimental studies
10.Intervention and evaluation

Uses of epidemiology

Description of health status of populations
Description of the natural history of diseases
Identification of causations
Evaluation of clinical signs, symptoms and decision analyses (clinical epidemiology)
Evaluation of interventions

What is clinical epidemiology?

Clinical epidemiology is the application of epidemiological principles and methods to the practice of clinical medicine (Beaglehole et al 1993). Clinical decisions should be based on sound scientific evidence (Evidence Based Medicine); this is the main justification for clinical epidemiology. EBM is a method of basing clinical decisions on the best available scientific evidence. The main areas of study in clinical epidemiology are: definitions of normality and abnormality, validity and accuracy of diagnostic and screening tests, natural history and prognosis of diseases, effectiveness of therapies, and prevention in clinical practice.

Classics in epidemiology

Epidemiology is a young science. It became established as a distinct, systematized body of knowledge only after the Second World War. The period from 1940s to 1970s is considered as the “golden era” in the evolution of epidemiology. A few large studies (particularly those involving smoking and lung cancer) provided the impetus to the growth of epidemiology and the tremendous improvement in epidemiologic methods. These are some classics in the field:

1.Smoking and lung cancer: The association between smoking and lung cancer is now considered almost causal. Since the first epidemiological studies published in the 1950s, several studies have demonstrated the association between smoking and lung cancer. In particular, studies by Doll and Hill are considered classics (Doll & Hill 1964). Their seminal work also spurred work on other chronic diseases like CAD, stroke, etc.

2.The Framingham Heart Study: Few studies are as famous as the Framingham Heart Study (FHS). The study began in 1948 and is still going strong 50 years later (Messerli 1998). The study was done to identify risk factors for CAD and is a classic cohort (longitudinal) study. Framingham is a town in Massachusetts (population of 28,000 when the study began). Thousands of the town residents were examined for CAD and risk factors. Subsequently, they were offered complete examination every 2 years since the study began. As new types of investigations appeared on the scene, they have been added to the examination. The study findings have emerged in a large series of reports over the years (e.g. Kannel WB, et al 1961) and have contributed tremendously to our understanding of CAD and its risk factors. More than 1000 articles from FHS have been published to date. The project has cost the American government $43 million. Analysis of the Framingham data also paved the way for the evolution of complex statistical modeling techniques like multivariate analyses.

3.Polio Vaccine Field Trial: The largest formal human experiment ever was done when the Salk polio vaccine was put through a field trial in 1954, with nearly a million school children as subjects. The study clearly demonstrated the protective efficacy of the vaccine and provided the basis for an eradication program.

References & further reading

Last JM. A dictionary of epidemiology. 2nd ed. Oxford, Oxford University Press, 1988.
Tyler CW, Last JM. Epidemiology. In: Last JM, Wallace RB. Editors. Maxcy-Rosenau-Last Public Health & Preventive Medicine. 13th edition. Appleton & Lange,1992.
Friedman GD. Primer of Epidemiology. 4th ed. McGraw-Hill Inc, 1994.
Beaglehole R, Bonita R, Kjellstrom T. Basic Epidemiology. Geneva, World Health Organization,1993 .
Coggon D, Rose G, Barker DJP. Epidemiology for the uninitiated. 3rd ed. Oxford University Press, 1993.
Sackett DL. Clinical epidemiology: a basic science for clinical medicine. Boston, Little, Brown and Co, 1985.
Doll R, Hill A. Mortality in relation to smoking: ten year’s observations of British doctors. BMJ 1964;1:1399-1410 and 1460-1467.
Kannel WB, et al. Factors of risk in the development of coronary heart disease: six-year follow-up experience: The Framingham study. Ann Intern Med 1961;55:33-50.
Messerli FH, Mittler BS. Framingham at 50. Lancet 1998;352:1006.
Rothman KJ, Greenland S. Modern Epidemiology. 2nd Edition. Philadelphia:Lippincot-Raven, 1998.
Greenland S. Evolution of Epidemiologic Ideas. Epidemiology Resources Inc, 1987.
MacMahon B, Trichopoulos D. Epidemiology: Principles & Methods. Second Edition. Little Brown and Company, 1996.

Epidemiology Links

Centers for Disease Control and Prevention (CDC)

CDC offers full text articles from the MMWR, Emerging Infectious Diseases, public information on diseases, prevention guidelines, traveling, publications, health statistics, funding opportunities, employment, and information sources.

www: http://www.cdc.gov

CDC WONDER (CDC)

CDC WONDER offers public health data sets to search, including mortality, SEER, and vital statistics data. It also allows communication with the CDC staff.

WWW Virtual Library: Epidemiology Page

The WWW VL Epidemiology site is part of the Virtual Library created by the World Wide Web Consortium at MIT and is a non-commericial listing of Web resources in epidemiology. The page is widely indexed and provides a comprehensive up-to-date resource listing. It is maintained as a public service by the Dept. of Epidemiology and Biostatistics, University of California San Francisco.

Epidemio-l (Epidemiology listserv)

This listserv discusses methodological issues related to epidemiology.

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Clinical-Trials (listserv)

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EPIVET-L (Veterinary epidemiology listserv)

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Public-Health listserv

This discussion group focusses on epidemiology and other public health topics for public health professionals. It’s a wonderful way to stay in touch with public health workers in the UK.

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Evidence-Based-Health listserv

This group discusses how to critically evaluate the literature, announces meetings and courses, and debates the controversies.

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Cochrane Collaboration

The Collaboration tracks systematic reviews of clinical trials in order to provide evidence for the best medical practice. This site explains the review process and links to the Collaboration sites.

SAS Institute

SAS maintains a public server to provide corporate information, software explanations, and user help.

www:http://www.sas.com

#012#Stat-l (Statistics) listserv

A very busy listserv that provides debates and assistance to statisticians, epidemiologists, and students regarding statistical theory and application in different fields, including health.

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American Public Health Association

A leading public health association with plenty of useful information and web links on epidemiology and public health.

www: http://www.apha.org

Dr. Madhukar Pai, MD, DNB
Consultant, Community Medicine & Epidemiology
Email: [email protected]