Objectives of Epidemiology (With Real-World Examples)

Epidemiology is the study of health issues at the population level which can provide information not available at the individual level.

The ultimate goal of epidemiology is to improve health — lower the risk of death and increase the quality of life — by refining preventive measures and treatments of diseases.

The objectives of epidemiology can be divided into 2 parts:

  1. Providing a basis for policy making and allocation of resources, by:
    • Discovering patterns and trends in health problems.
    • Predicting the number of cases of a disease and its distribution in the population.
  2. Helping with diagnosis, prognosis, and selection of treatment, by:
    • Explaining the etiology of disease.
    • Studying the course of a disease quantitatively from onset to outcome.
    • Assessing preventive measures and treatment options.

Below we will discuss each of these points in details.

1. Providing a basis for policy making and allocation of resources

Epidemiological research provides information that can be used to specify the priority for investigation and action.

This can be done by:

To identify the importance of a given health problem, many studies set their objectives to measure its incidence, prevalence and mortality.

Also obtaining relative frequency of cases within subgroups will help identify high-risk groups on which we should focus prevention or apply an appropriate solution.

Real-world example — Discovering patterns in obesity distribution:

In 2018 Datar & Nicosia found that exposure to a community where obesity is prevalent is associated with higher BMI and odds of overweight.

The absence of evidence for self-selection and shared environment as possible explanations suggests that obesity may be spread by social contagion.

If true, this will not only impact how obesity is viewed in society but also the strategies used to prevent it.

1.2. Predicting the number of cases of a disease and its distribution in the population

This is crucial for instance to determine the number of public health professionals needed and how they should be assigned.

Real-world example — Predicting Dengue cases:

The medical company Aime Inc (Artificial intelligence for medical epidemiology) is using data on factors that influence the behavior of dengue carrying mosquitoes to predict an outbreak of the disease 3 months in advance with high accuracy [source].

2. Helping with diagnosis, prognosis, and selection of treatment

Since Hippocrates (460 B.C.), people have been trying to rationalize the way we think about and treat disease.

Epidemiology provides us with a rational basis for diagnosing and treating health problems.

This rational framework works through:

2.1. Explaining the etiology of disease

Epidemiology can help identify the causal agent and the modes of transmission of diseases which are key for diagnosing as well as finding the appropriate treatment.

Infectious diseases in general have a more direct and clear cause — the pathogen — compared with non-communicable diseases that have genetic components and environmental risk factors which increase the risk of having the disease.

Real-world example of identifying the cause of a disease — Framingham Heart Study:

This is a famous epidemiological study which began in 1948 and followed ~14,000 residents of a town called Framingham in Massachusetts to study cardiovascular disease.

Much of what is now known today about risk factors of heart disease is based on this study.

Based on results from this study, routine medical checkups now include checking for: blood pressure, smoking, cholesterol levels, etc. [source: NIH]

Real-world example of identifying the mode of transmission of a disease — John Snow and cholera:

In 1854, the mechanism by which cholera was transmitted was not known.

John Snow, an English physician, examined data that he collected on the outbreak of cholera in London and observed that cases of cholera were concentrated around the Broad Street pump.

His observation was in line with his theory that cholera was a waterborne disease.

The outbreak ended by removing the handle of the pump thus preventing people from drinking the contaminated water. [source: Wikipedia]

2.2. Studying the course of a disease quantitatively from onset to outcome

Understanding the natural history of the disease in quantitative terms is important for comparing the effects of possible treatment options or interventions.

Epidemiology can help by quantifying the mortality of a disease, its duration and impact on the quality of life of patients.

Real-world example — BPI — A pain assessment tool for cancer patients:

Using epidemiological principles, the pain research group of the WHO collaborating center for symptom evaluation in cancer care has developed the Brief Pain Inventory (BPI).

This tool measures both the pain intensity and its interference with the patient’s life.

The BPI has been translated into many languages and used across cultures. It has been used both to assess pain and to compare pain treatments. [source]

2.3. Assessing preventive measures and treatment options

Epidemiology also plays a role in evaluating and comparing screening tests, prevention programs, medical procedures and drug therapies.

Real-world example — Comparing Laparoscopic and open surgery for rectal cancer:

To compare these approaches, a study randomly allocated 204 patients with rectal cancer to receive either open or laparoscopic surgery.

The result was that laparoscopic surgery had similar outcome to open surgery with less side effects.


  • David Celentano, Moyses Szklo. Gordis Epidemiology. 6 edition. Elsevier; 2018
  • Aschengrau A, Seage GR. Essentials of Epidemiology in Public Health. 4 edition. Burlington, MA: Jones & Bartlett Learning; 2018
  • Friis RH, Sellers T. Epidemiology for Public Health Practice. 5 edition. Burlington, Mass: Jones & Bartlett Learning; 2013

Further reading