Unit 1: Study Session 1: What is Epidemiology?

Introduction to the terminology, definitions and uses of epidemiology in research, clinical practice and community/district health management.


This study session introduces epidemiology, its terminology, definitions, and its different uses in research, clinical practice and community or district health management. In the course of the session, you will also focus on reading graphs and tables. This is an essential competence for studying in this field. The session is intended to provide you with a foundation for understanding and engaging in Descriptive Epidemiology. You are certain to discover that you have already encountered epidemiological information in some form or another.

Epidemiology will help you to answer questions like these:

Examples will be used to illustrate how health activities are measured or monitored. Having understood these examples, we hope you will be able to analyse similar sets of data from elsewhere in the country and internationally.

The careful completion of the tasks in this session is important as this unit provides the foundation that you will need for the rest of the module.


  1. Learning outcomes of this session
  2. Readings
  3. Clarify key concepts used in epidemiology
  4. Explore your experience with epidemiology
  5. The applications of epidemiology
  6. Interpreting graphs and tables
  7. Session summary

Timing of this session

This session contains three readings, one of which is a glossary of terminology and eight tasks. It should take you up to three hours to complete depending on your familiarity with the terms and with graphs and tables.


 By the end of this unit you should be able to:

Health Measurement Outcomes

  • Define common epidemiological terms and concepts.
  • Describe the role of epidemiology in providing critical information on key health conditions.
  • Recognise contextual influences on epidemiology in Africa.
  • Develop a conceptual framework to describe community health.
  • Critically review the technical content of scientific reports.

Academic Learning Outcomes

  • Develop working definitions of key terms and concepts.
  • Locate relevant data from complex tables and data sheets.
  • Adapt a conceptual framework to your needs.
  • Develop a strategy for effective reading and critique of articles.


The three readings for this session are listed below. You will be directed to them in the course of the session. The third reading is a glossary of terms that you may want to refer to during this session and later in the module.

Author/s Publication Details
Katzenellenbogen, J.M., Joubert, G. & Abdool Karim, S. S.
(1997). Ch 1 - Introduction. In Epidemiology: A Manual for South Africa. Cape Town: Oxford University Press: 3 - 9.
Beaglehole, R., Bonita, R. & Kjellstrom, T. (1993). Ch 1 - Wat is Epidemology? In Basic Epidemiology.Geneva: WHO:1 - 11
Vaughan, J. P. & Morrow, R. H. (1989). Ch 14 - ABC of Definitions and Terms. In Manual of Epidemiology for District Health Management. Geneva: WHO: 155 - 167.


Like many other areas of health and medicine, the study of how health and disease is measured has generated a variety of new terms and concepts. It will be important to develop your own working definitions in order to read the material contained in this module more effectively and critically. The following tasks help you to do this.

Start off by previewing the Katzenellenbogen, Joubert and Abdool Karim and Beaglehole, Bonita & Kjellstrom. You will find guidance on how to preview texts in the SOPH Academic Handbook, Section 5.3.3. Previewing helps you to read with focus and understanding.

Broadly, the two texts present a definition of epidemiology, its historical origins, current applications and achievements, its role in Public Health research and its particular value in the African context. The reading by Katzenellenbogen, Joubert & Abdool Karim provides an overview of what epidemiology entails, how it is applied in South Africa and what impacts on it in the African context, while the chapter by Beaglehole, Bonita & Kjellstrom takes a more historical approach in its introduction, and identifies some of the achievements of epidemiology. This reading provides a useful set of study questions on page 11. Bear them in mind while you read, then try to answer them.

Take note of the different branches of epidemiology described on page 5 of     Katzenellenbogen, Joubert & Abdool Karim, remembering that this module focuses on Descriptive Epidemiology. Focus on the challenges faced by epidemiology which are listed at the end of this reading, on page 9; these may affect you in your work.


  • Katzenellenbogen, J.M., Joubert, G. & Abdool Karim, S.S. (1997). Ch 1 - Introduction.In Epidemiology: A Manual for South Africa. Cape Town: Oxford University Press:3 - 9.


  • Beaglehole, R., Bonita, R. & Kjellstrom, T. (1993). Ch 1 - What is Epidemiology? In Basic Epidemiology.Geneva: WHO: 1 -11.


When previewing, it is helpful to identify key questions to which you would like answers. If I were reading these two texts, I would try to find answers to the first two questions, as a way of focusing my reading:

  1. What do epidemiologists do?  (Figure 1.2 on page 4 may be helpful).

  2. What is the main difference between the work done by clinicians and epidemiologists?

  3. Once you have taken these notes, write your own definition of epidemiology.


The work of epidemiology differs most fundamentally from that of clinical health workers in that it addresses health issues at the population level, whereas most health workers are involved in treating individuals or small groups of patients. The information built up over decades of epidemiological research has provided clinicians with fundamental information about the natural history of the diseases they treat, about what causes them, what interventions work best and also about the distribution of disease and risk factors in the population at large.

The word epidemiology is derived from the Greek epi (upon) and demos (people). Most people would agree on a definition of epidemiology something like this: “The study of the distribution and determinants of health-related states or events in specified populations and the application of this study to the control health problems” (Last, 1988, in Beaglehole, Bonita & Kjellstrom, 1993: 3).

The readings offer a variety of illustrations of epidemiology and its application to the assessment of different health and disease problems over time. Have you encountered any of the examples described before?

In the next task you will check and expand your understanding of key concepts used in epidemiology. The following reading lists some epidemiological terms.


  • Vaughan, J. P. & Morrow, R. H. (1989). Ch 14 - ABC of Definitions and Terms. In Manual of Epidemiology for District Health Management. Geneva: WHO: 155 - 167.


  1.  Underline any terms or concepts that you have come across for the first time, or which are unclear to you.
  2.  Try to write down an explanation of these terms using your own words. Check their meaning in any of the three readings for this session. If these texts do not adequately clarify the meaning, consult Chapter 14 of Vaughan & Morrow (1989) or a good dictionary, e.g. Chambers 21st Century Dictionary, 1996.


Your list of new terms might have included the following concepts:


Make sure that you are really clear about what these concepts mean as it is difficult to study or to read effectively without this clarity. Consult a more experienced colleague or the references if you are unclear about any of the terms.


Most people already know something about the subject they are starting to study and the same is probably true for you as you begin this epidemiology module. This section

aims to identify areas of your work experience where you may already have encountered or even done some epidemiology.


As a Public Health worker, it may be important for you to know the extent to which a particular health condition affects people in your district, e.g. the percentage of a district population affected.

  1.  List 2 - 3 health conditions encountered in your area or in the course of your work, for which there is information available. Try to find out what proportion of people in your area are affected by these conditions.

  2. Where does this information come from?

  3.  What does this information tell you about the health status of your community?

  4.  If you work with this information, does that mean you are doing epidemiology? Explain.

  5. What sorts of decisions are made in your workplace using this information?


Whether they know it or not, most health workers work with or come across information describing the health or illness of a population in the course of their work. This is one of the four main areas of epidemiology. Perhaps you simply have to record the number of cases of diarrhoea seen at a clinic, or the age and weights of children with malnutrition. All these pieces of information together provide a picture of the health status of your community, and they all contribute to the process called epidemiology. So perhaps without recognizing it, you already know something about epidemiology because you have already been doing it.


  1. Make a list of the different types of health information you encounter as a health worker and make a note of what you actually do with this information.
  2. Which of these activities fit the definition of Descriptive Epidemiology as you expressed it in Task 2?
  3. How do these epidemiological activities contribute to the Public Health work of your organisation or institution?


Epidemiology has provided us with a very strong research basis for understanding health and disease events and patterns in populations. You may have recognised that information obtained from epidemiology research or data collection can guide your understanding of health events, or help you to make decisions. Epidemiology provides some very powerful tools for tasks such as problem identification, decision-making or even programme evaluation. The sad thing, however, is that it appears to be so under-utilised in the health bureaucracies of Africa.

Epidemiology can provide data that shows improvements in health status and may also identify serious failures or pitfalls in the health system. It may also be ignored or even deliberately concealed. This makes it a potential political football. Worse still, it may point to areas of causation located in underdevelopment, poverty and political incompetence. To address these situations requires massive resources and political will. See also Katzenellenbogen, Joubert & Abdool Karim, 1997: 6 - 7.


From fairly focussed beginnings (which you read about in Beaglehole, Bonita & Kjellstrom, 1993) the field of epidemiology has grown to include and influence a wide range of clinical and Public Health activities. Some of the more prominent applications of epidemiology are identified in the next task.


  1. From your reading of the texts, identify at least four main roles or uses for epidemiology. Prepare a short written description of each of these applications.
  2. Identify one example of each of these main uses of epidemiology from your own experience or from the readings. Beaglehole, Bonita & Kjellstrom (1993) contains several examples.
  3. Explain how the knowledge in the example can contribute to an important Public Health strategy or decision.


  1. A particularly neat, simple summary of the ways in which epidemiology has contributed to our understanding and practice of Public Health is found in Figure 1.2 on page 4 of Beaglehole, Bonita & Kjellstrom (1993). Here the main uses of epidemiology are grouped into four categories, namely causation, the natural history of disease, description of the health of populations and the evaluation of interventions. Note that these have relevance in both the clinical health care arena as well as in Public Health.

  2. Katzenellenbogen, Joubert & Abdool Karim (1997) describe the uses of epidemiology in slightly different terms, relating the two broad areas of research and Public Health epidemiology to the local South African context.

  3. In the section entitled Achievements of Epidemiology, Beaglehole, Bonita & Kjellstrom (1993) (pages 4 - 9), provide several examples to illustrate the uses of epidemiology. Here are some examples of the different categories of epidemiology and their contributions to Public Health strategies:

    • One well-known example of using epidemiology to establish causation is the link between smoking and deaths due to lung cancer. Causation studies provided this information and numerous anti-smoking or smoking cessation programmes have been based on the premise that there is a link between smoking and death from lung cancer.

    • In order to manage our TB programmes, we need to know what proportion of the population is affected in each area. A TB prevalence of 850/100 000 in a specific area tells us there is a massive problem to be addressed here.

    • New antiretroviral drugs are a major new area of research which aims to evaluate which medications work best at controlling AIDS. These and many other interventions are the subject of epidemiological trials.

    • Virtually every immunisation programme owes its existence to intervention studies that established the efficacy of immunisation against infectious diseases such as measles, tetanus, smallpox, etc

    • The natural history of SARS, a very recent disease outbreak, is only now becoming clear, as case records from numerous cases around the world are collated and reviewed.

    • Both TB and HIV/AIDS are conditions where it is critical that we understand the natural history of these diseases. They both have long periods in which they exist as sub-clinical infections, that is, before they produce symptoms that the patient or health worker can detect. During this period, patients are unlikely to seek treatment and can infect their partners or those around them.

    • Public Health workers are particularly concerned with the size and distribution of different diseases or health risks in the population, such as what proportion of the population has TB or how many new cases are occurring each month. This guides decisions as to how to respond, e.g. provide more TB beds, improve treatment adherence, extend BCG programmes, etc.

Having clarified some of the concepts and the role of epidemiology, the final section of Study Session 1 concentrates on another essential foundational block of epidemiology, namely reading and interpreting information presented in graphs and tables.


Epidemiological texts often make use of tables, graphs and other illustrations to present information. Beaglehole, Bonita & Kjellstrom (1993) include several graphs and tables that support the text. You need to be able to read and interpret graphs and tables with ease. Here are some examples to check your skills and to practise on. If you have difficulty, ask a colleague to help you to develop a simple strategy for reading them.

Make sure that you understand the concept of ratio and rate before you start (Katzenellenbogen, Joubert & Abdool Karim, 1997: 15 - 17).

We usually want to compare disease rates across different communities or areas. However, each community has a different size and also a different number of people that are ill. A percentage is an example of a rate multiplied by 100. When we deal with population figures that may be fairly large, we usually calculate rates out of

1 000 or 100 000 because the figures are then easier to grasp.


Community A might have 250 people with TB. Community B may have only 100 cases of TB. So far we can see there is more TB in Community A.

If I tell you that Community A has a population size of 123 500, this means

250/123 500 people there have TB. Divide this number 250, by 123 500 using a calculator and you will get 0.002. Multiply this by 100 and you get 0.2%. If instead you multiply by 1 000, you will get a prevalence of 2/1 000 cases of TB. Alternatively, you could multiply this by 100 000 to get a rate of 200/100 000.

If Community B has a population of 25 000, this means their TB prevalence is

100/25 000. Divide this and you get 0.004. Multiply this by 100 and you get 0.4%. If you multiply by it 1 000 you will get a prevalence of 4/1 000. This is double the prevalence in Community A, so Community B actually has a much bigger TB problem than Community A.



Beaglehole, Bonita & Kjellstrom (1993) (page 1, Table 1.1) provide summary data on deaths in a cholera outbreak that took place in two districts of London, in 1851.


Beaglehole, R., Bonita, R. & Kjellstrom, T. (1993). Ch 1 - What is Epidemiology? In Basic Epidemiology. Geneva: WHO: 1 - 11.


  1. Compare the number of deaths from cholera in the districts of Southwark and Lambeth.

    There are two ways to express this, as a difference and as a ratio.To calculate the difference, subtract the smaller figure from the larger one, i.e Lambeth from Southwark.

  2. However, this does not usually tell us how serious the problem is because of the differences in population size in the districts being compared. Calculating the proportion – or ratio – of the population of Southwark that died from cholera, and comparing that to the ratio of cholera deaths in Lambeth is of greater value to Public Health workers.
  3. Roughly how many more deaths were there in Southwark than Lambeth?
    20 times more o; 10 times more o; 40 times more o; 80 times more o
  4. Compare the populations of Southwark and Lambeth. How many times bigger was the Southwark population than the Lambeth population?
    20 times bigger o; 8 times bigger o; 2 times bigger o; 50 times bigger o
  5. Why is it necessary to calculate the death rate per 1 000 of the population, as shown in the last column? From the figures provided, can you work out how to calculate the death rate?
  6. What do these death rates tell us about the risk of getting cholera in these two districts in 1851? Would you rather have lived in Southwark or Lambeth?
  7. Which column in the table contains the most important information? Why do you say so?


  1. The difference in the number of deaths in the two areas is 826, but this tells us very little except that there were more deaths in Southwark.
  2. To find out how many times more deaths there were in Southwark, you divide the smaller number of deaths (18) into the larger number (844), i.e. how many times does 18 go into 844? You will find that there were over 40 times more cholera cases in Southwark than there were in Lambeth.
  3. For the epidemiologist, the number of deaths (on its own) means very little unless we recognise that the population sizes being compared are very different. This is why we use a rate to compare them. Divide Southwark’s population of 167 654 by Lambeth’s population of 19 133 and you get a rough figure of 8. Southwark therefore had a population 8 times greater than Lambeth.
  4. The death rates are calculated by dividing No. of Deaths by Population in 1851 and multiplying by 1 000. In Southwark, (844 / 167 654) * 1 000 = 5.0 (or 5 per 1 000), whereas in Lambeth it would be 18 * 19 133 = 0.9 (or less than 1 per 1 000). The epidemic is therefore much more serious in Southwark.
  5. A higher proportion of people got cholera in Southwark. If you lived in Southwark, the probability (risk) that you would be one of the victims of cholera was much higher than if you lived in Lambeth.
  6. The main result in this table is to be found in the column entitled Cholera death rate per 1000 population.

The role of water supply in causing cholera and the use of geographical mapping to trace the cause will be explored in Unit 2 session 4, in a description of the 1851 London cholera epidemic by John Snow.

Making Sense of a Graph

Now turn to Beaglehole, Bonita & Kjellstrom (1993), page 2, Figure 1.1. The reading illustrates a relationship between deaths from lung cancer amongst British doctors between 1951 and 1961 and their levels of cigarette smoking activity.

Two important elements found in graphs are variables and axes. A variable is a characteristic that can be measured. There are two in this example: the number of people who died of lung cancer, and the number of cigarettes each person smoked per day. In Figure 1.1 the two variables are plotted as follows: the y-axis (vertical) shows how many British doctors died of lung cancer between 1951 and 1961 out of every 1 000 doctors who died during this period. The x-axis (horizontal) indicates the number of cigarettes each of those doctors smoked per day before they died.

Your task is to interpret the graph and determine what kind of relationship there appears to be between the two variables. Have a look at Figure 1.1. According to its title, this graph looks at all British doctors who died of lung cancer between 1951 and 1961. It groups these doctors according to how many cigarettes they smoked each day. For convenience, it converts these into a rate, i.e. the number of doctors who died of lung cancer out of every 1 000 doctors who died. For example 1.5 out of every 1 000 doctors who died of lung cancer smoked 20 cigarettes per day.

Here is some guidance on how to read the graph. Focus on the black dots plotted on the graph. Find the dot that represents those doctors who smoked 15 cigarettes per day and experienced a death rate of 1.0. This death rate means that among the doctors who smoked 15 cigarettes per day, one doctor in 1 000 died of lung cancer. The fourth dot from the left represents those doctors who smoked 15 cigarettes per day. A horizontal line drawn from this dot onto the y-axis shows that this group of doctors experienced a death rate of 1.0 per 1 000. Now practise reading the graph.


  1. What is the death rate for doctors who smoked:
    • 10 cigarettes per day?
    • 20 cigarettes per day?  
    • 30 cigarettes per day?
    • 40 cigarettes per day?
  2. What do you notice about the association between higher daily cigarette consumption and the lung cancer death rate?
  3. Look at the straight line inserted across the graph. Notice that it is very close to all the dots and almost connects them together. The line was inserted to illustrate the relationship between the information on the x-axis and the information on the y-axis. What can such a straight line tell us about the relationship between the two variables, i.e. death rates and cigarettes per day?
  4. This graph is an example of an x-y scatter plot. What do you think this means? What is the purpose of such a graph?


  1. You should have determined the death rate for doctors who smoked:
    • 10 cigarettes per day as about 0.75 per 1 00
    • 20 cigarettes per day as about 1.6 per 1 000
    • 30 cigarettes per day as about 2.4 per 1 000
    • 40 cigarettes per day as about 3.3 per 1 000
  2. Deaths from lung cancer are strongly associated with the number of cigarettes smoked daily. Because the line slopes up toward the right hand side, it means that there are more heavy-smokers who die of lung cancer than light-smokers. Put another way, the more cigarettes you smoke per day, the more likely it is that you will die of lung cancer.
  3. The most striking characteristic of this graph is that the dots form an almost completely straight line. The line has been added to the graph to illustrate this. When you see this kind of “straight line relationship” you can usually assume that information on the vertical y-axis is strongly associated with the information on the horizontal x-axis.
  4. An x-y scatter plot is a very simple and neat way of showing whether there appears to be a relationship between two variables, the one indicated on the x-axis and the other on the y-axis. If the dots cluster together in some part of the graph, there may be an association of some kind between the variables. If they are spread all over the graph, it is very unlikely that there is any association present.

 Now try making sense of another kind of graphical illustration.


Take a look at Beaglehole, Bonita & Kjellstrom (1993), page 10, Figure 1.5 which

illustrates some important features of the AIDS epidemic. Study this figure and try to

identify what it tells you about the AIDS epidemic.

  1. What is the main point this illustration is trying to make? Why is HIV/AIDS called the hidden epidemic?
  2. Why have the authors chosen to use a pyramid shape to represent what is happening with the HIV/AIDS epidemic?
  3. What are the consequences of the hidden nature of HIV/AIDS for the public? In what way does this affect our ability to accurately measure/monitor the size of the epidemic?


Figure 1.5 demonstrates how a good choice of graphical image can emphasise the main point the writer is trying to illustrate. The pyramid is a powerful and widely recognised symbol, with a prominent point at the top and a broad solid base below. Others have used the image of an iceberg floating with its tip above water and large bulk below.

As the title suggests, the illustration is trying to highlight one main characteristic of the AIDS epidemic, i.e. the fact that most people with AIDS are not identifiable because they are either in the sub-clinical phase of the disease and do not know they have it, or they are not sick enough to report to a clinic or doctor where they can be diagnosed. Like the iceberg or pyramid, there are far more invisible cases (below the shaded plane) than reported, visible cases of AIDS in the population. This makes accurate measurement of the actual extent of the epidemic in the population very difficult. This in turn makes it very difficult to lobby for resources or run programmes to respond to the epidemic. Many people still struggle to believe it is actually a major problem.


In this session, you have explored the meaning of certain key concepts use in epidemiology, considered its role in Public Health and its application in your own work context. You have also practised your reading skills both of texts and graphical illustrations.

In the next session, we introduce a set of important questions you need to ask in order to understand and respond to a Public Health problem. This set of questions should become part of your own systematic framework for assessing the epidemiological profile of a given community or event for which you have responsibility.

Citation: Unit 1: Study Session 1: What is Epidemiology?. (2008, May 21). Retrieved November 24, 2014, from UWC Free Courseware Web site: http://freecourseware.uwc.ac.za/freecourseware/school-of-public-health/measuring-health-and-disease-1-introduction-to/course-content/unit-1-1/unit-1-what-is-a-descriptive-epidemiology.
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