What is epidemiology?

DEEpidemiology is the study of the quantitative investigation of the factors that influence the state of health of the population. Epidemiological studies help identify those people more or less likely to have certain diseases. It also explores whether disease rates change over the years and in which areas certain diseases are particularly prevalent.

Epidemiological studies compare different populations to provide insightful results. These conclusions from epidemiological studies are very important for the management of the health system. Thanks to this research, it is possible to observe the health status of a population. Thus, based on epidemiological findings, public health programs for the early detection of diseases can be established.

Clinical medicine also benefits from epidemiology. Because epidemiology is not only concerned with infectious diseases and epidemics, but with all sorts of diseases. The epidemiological approach is often used to develop reliable guidelines and provides physicians with advice on which diagnostic tests and treatments are useful.

Epidemiology is mostly involved in designing research studies, data collection and analysis of results. The study results will be communicated to support decision makers in healthcare, clinics and the public.

What skills are required to carry out epidemiology?

The field of epidemiology includes many different aspects. Epidemiological studies usually require the expertise of

  • doctors
  • biologists
  • biochemists
  • other scientists

to explore the biological aspects of the disease. Many epidemiological studies are based on the experience of biostatisticians and information technologists. In this way, appropriate methods of data collection are designed to perform a statistical analysis in the fastest way possible. In addition, social scientists are often involved to identify important topics for the perception of a particular clinical picture and to assess how the population might react to it.

Since epidemiology requires many different skills and scientific knowledge, the background and training of epidemiologists is also very different. For example, some epidemiologists start their careers as laboratory scientists in chemistry or microbiology and only later begin epidemiological studies.

Many doctors and nurses are also working in clinical practice and finding their way into epidemiology and public health to treat the entire population and focus on the patient population. Other co-workers, such as biostatists, often begin their education in statistics and mathematics before later becoming involved in epidemiology. There they develop suitable study designs and methods of data analysis.

Epidemiology in history

One version of the history of epidemiology is that the famous Hippocrates, whose oath is worn by doctors almost everywhere in the world, was an epidemiologist. Hippocrates already hypothesized that some diseases are caused by environmental factors and affect the population.

However, there is another variant of the story: before the 17th century, there were no comparisons between populations that considered various diseases. It was not until the seventeenth century that John Graunt conducted a series of analyzes on London’s newly introduced „Bill of Mortality,“ the weekly statistics on deaths in London. For the first time, the most frequent causes of death were systematically determined. The various causes were thus published every week as an early warning signal for the onset of a disease. From today’s perspective, the Bill of Mortality showed that overall mortality remained constant while mortality peaked at the time of the plague. This suggests that the environment has an impact on the mortality rate.

Another pioneer in epidemiology was James Lind. The Scottish doctor discovered the treatment of scurvy with lemon juice. In the Lind experiment, he divided twelve scorbut-sick sailors into groups. Two people were always given different foods for their diet:

Group 1: 1 liter of cider

Group 2: 25 drops of sulfuric acid

Group 3: 6 spoons of vinegar

Group 4: ¼ liter pint

Group 5: 2 oranges and 1 lemon

Group 6: spice paste and barley water

Patients in group 5 – oranges and Lemon – were back in action after a week and almost completely healthy.

Epidemiology from the 19th century

About 200 years after Graunt, epidemiologist Jon Snow compared the mortality of cholera between clients of two London-based companies. His study confirmed the hypothesis that cholera is somehow related to contaminated drinking water. In the end, his research led to the removal of the water pump handle on Broad Street. At the time, that was a controversial move, as there were many more theories about the cause of cholera. Meanwhile, it was proven that Jon Snow was right and providing clean and safe drinking water was one of the key elements of improving health during the 19th century.

Another important example of the epidemiology of the 19th century is the study by Dr. med. Pierre Louis on the effectiveness of bloodletting, also called bloodletting, for the treatment of pneumonia. Furthermore, Ignaz Semmelweis proved the effectiveness of hand washing in the prevention of puerperal fever.

In the mid-twentieth century, several epidemiological studies attested that smoking could increase lung cancer risk. Some epidemiologists like Wynder and Graham or Doll and Hill compared the frequency of smoking in lung cancer using carefully selected controls. Others compared the occurrence of lung cancer in smokers and non-smokers. These controls were highly controversial among some scientists and the tobacco industry. However, epidemiological studies have over the years confirmed numerous negative health effects of smoking, such as heart disease and various types of cancer.

Epidemiology in action

The application of the epidemiological method is important in many areas as epidemiologists are diverse. Epidemiologists can be used in hospitals or local health care facilities, but also in government or commercial companies such as the pharmaceutical industry. All these areas have one thing in common: They work to examine the state of health in different groups of people, making comparisons over time and place. Laboratory scientists and research physicians often use experimental methods that focus on a specific risk factor or event. So all other risk factors can be checked in detail. This happens among other things by a random generation, which means it is decided randomly, who receives which treatment.

In contrast, epidemiologists can study multiple diseases and risk factors for a disease simultaneously. This often requires refined study designs. So epidemiology always tries to deal with many determinants of diseases in the population. Often, epidemiologists are busy isolating the link between a risk factor and a particular health outcome, while considering other important relationships in people’s daily lives. Thus, epidemiologists are not limited to factors that are measured on an individual level. Instead, they also measure community-level factors and incorporate all sorts of information into their analysis. They also take into account that some factors at different stages may have different effects and that these effects of exposure at a younger age may manifest only at a higher age.

Important information in epidemiology

While important and useful information from laboratory studies can be obtained for treatment, these results are not always generally applicable to the entire population. Here the epidemiology has the advantage that it examines in more detail what happens in which population. In addition, many health-related issues can not be addressed by experimental randomization in humans, such as the health effects of smoking.

Under certain circumstances, epidemiologists can apply randomization in the community. This works, for example, to evaluate the potential benefits and disadvantages of screening for cancer screening. In doing so, they can randomize parts of the population that are screened – or not – to observe subsequent experiences with cancer detection and prognosis. However, this type of study is rather unusual due to the large sample size and the long period of follow-up.

Instead, epidemiologists are more concerned with investigating the effects

the health of people, but without the ability to randomly put people on risk categories. This poses the biggest challenge for epidemiologists. Nonetheless, epidemiology is crucial for the detection and treatment of epidemics in infectious diseases such as influenza, HIV or measles.

The 5 important topics of epidemiology

1. How do you count?

It is an important question how epidemiologists count the number of people who are at risk for disease and those who already have a disease. These counts are used to calculate disease risks in different parts of the population or for different periods of time.

The goal of epidemiologists is to identify groups of individuals and calculate their risk of disease. Different factors are important for this: the number of people suffering from the disease and the number of people in the part of the population studied by the epidemiologists.

For example, the risk of disease is studied in men aged 50-59 years. The number of men in this age group who may have or develop the disease being studied is the denominator of a risk estimate. The number of people who actually contract the disease is the risk counter. For example, suppose that this study involves 1,000 men in the 50-59 age group and 15 of these men have lung cancer for over 10 years. In this case, the 10-year lung cancer risk in the population would be 15/1000 or 1.5%.

2. How do you compare?

In order to determine and determine the causes and effects of diseases, counts must be compared. Thus, the incidence of coronary heart disease is compared between persons with different characteristics. In this way, one learns to what extent the characteristics contribute to the incidence of diseases.

There are several ways to make such comparisons. Different study designs lead to different measurements to summarize the comparisons of the counts. The widely used measurements in epidemiology are:

  • risk ratio
  • risk difference
  • Odds ratio
  • Number of subjects

The study designs include cohort studies, case-control studies and cross-sectional and ecological comparisons.

3. Where do hazards arise for sources of error?

Count comparisons are susceptible to error in epidemiology, as often no true value is measured. Thus, in epidemiology, different forms of bias – that is a distortion of the result of a representative survey – are known. These deviations are categorized as follows:

Selection bias: Due to the selection of study participants

Information bias: Due to the way the information is used in the study

Screening Bias: Due to the peculiarity of the screening

4. What do epidemiologists see as the cause?

The most important step in epidemiology is the comparison of counts with causality statements: If a factor is considered causal, we assume that the frequency of the disease can be changed if that factor is changed. Therefore concepts and strategies are developed. The main goal is to decide if a particular factor is a cause or not. A cause causes something to happen, thus causing or preventing disease. When causes are detected, things can be changed as well.

Although philosophers have long talked about causes and are still talking about them, epidemiologists cling to an age-related pragmatic definition of a cause: „Something that reduces the incidence of disease by taking it away.“ This view points to the current dominant philosophy of thinking about causes in medical statistics and epidemiology based on potential outcomes and counterfactual thinking.

5. How to deal with causes?

Most diseases have several causes. Sometimes potential causes are so close to one another that it is tempting to mistake one cause for another: we believe that alcohol consumption is linked to lung disease, but it may also be that smokers drink more alcohol than non-smokers. At another time, the effect of the other is increased or decreased. For example, a mutation in a gene can lead to a higher frequency of disease, an environmental factor (eg smoking) can also lead to a higher frequency of the disease. When both causes come together, the resulting burden is much higher. This means that some people only get ill if they are exposed to both factors. The task of Ep

So idiologists also have to separate the effects of mixed causes and, at another point in time, assess their common effects or interactions.

Documents and Studies about Epidemiology

Recent Methodological contributions to clinical Trials – Jerome Cornfield

Bias in analytic research – David L. Sackett

Constructing vital statistics:
Thomas Rowe Edmonds and William Farr, 1835–1845

Origins and early development of the case-control study:
part 2, The case-control study from Lane-Claypon to 1950

Cohort studies: history of the method II. Retrospective cohort studies

Ecological Bias, Confounding, and Effect Modification

When Genius Errs: R. A. Fisher and the Lung Cancer Controversy

Asbestos Exposure and Neoplasia


Snow and Farr: a scientific duet

The changing assessments of John Snow’s and William Farr’s cholera studies

British Medical Journal

Reflections on the work of the Atomic bomb casualty commission in Japan

Assessment of the Protective Efficacy of Vaccines against Common Diseases Using Case-Control and Cohort Studies

Tobacco Smoking as a Possible Etiologic Factor in Bronchiogenic Carcinoma

Joseph Goldberger: An Unsung Hero of American Clinical Epidemiology

Changing images of John Snow in the history of epidemiology

Philip Morris

Basic Methods for Sensitivity Analysis of Biases

Statistical methods in epidemiology: Karl Pearson, Ronald Ross, Major Greenwood and Austin Bradford Hill, 1900–1945

Wolters Kluwer Health

Smoking and death rates\p=m-\report on forty-four months of follow-up of 187,783 men

Statistical Aspects of the Analysis of Data From Retrospective Studies of Diesease

III. Future Research and Health Surveillance

“On Prognosis” by William Farr (British Medical Almanack 1838; Supplement 199–216) Part 1 (pages 199–208)

“On Prognosis” by William Farr (British Medical Almanack 1838; Supplement 199–216) Part 2 (pages 208–216)

BMJ Publishing Group

Wolters Kluwer Health

Cohort analysis: W.H. Frost’s contributions to the epidemiology of tuberculosis and chronic disease

Tobacco Smoking as a Possible Etiologic Factor in Bronchiogenic Carcinoma

Interpretation and Choice of effect Measurs in Epidemiologic Analyses 1

Commentary: MRC Patulin trial

Elie Metschnikoff and his theory of an ‘instinct de la mort’

Cancer of the Breast—by Janet Lane-Claypon (1926): A Reanalysis

Estimability and Estimation in Case-Referent Studies

Ceteris Paribus: The Evolution of the Clinical Trial

Do sunlight and vitamin D reduce the likelihood of colon cancer?

Cohort studies: history of the method I. prospective cohort studies

British Medical Journal

Lessons from John Graunt

Sick individuals and sick populations

Commentary:Sick populations and sick individuals

History of bias

Public Health Reports

Tests of significance considered as evidence

“On Prognosis” by William Farr (British Medical Almanack 1838; Supplement 199–216) Part 1 (pages 199–208)

Classicsin Oncology Cancer Studiesin Massachusetts. 2. Habits, Characteristics and Environmentof Individualswith and without Cancer

October 1933

American Journal of Epidemiology

American Journal of Epidemiology

Apolipoprotein E isoforms, serum cholesterol, and cancer

Maximum Utilization of the life table Methode in Analyzing survival

Causality in epidemiology

Tumours of the Urinary bladder in workmen engaged in the Manufacture and use of Certain Dyestuff Intermediates in the British Chemical Industry

The changing assessments of John Snow’s and William Farr’s cholera studies

Cancer and Tobacco Smoking

Lung cancer and Tabacco consumtion

Royal Society Publishing

Developments in Theory and Quantitative Methods

In Defense of Case Reports and Case Series

Medical Practice

History of bias


Reflections on the work of the Atomic bomb Casualty Commission in Japan

Epidemiological Approaches to Heart Disease: The Framingham Study

Alcohol and coronary heart disease

Clinical trial of patulin in the common cold

Wolters Kluwer Health