Epidemiology 101: basic concepts

Dr Ike AnyaSpecialist Registrar in Public Health Medicine, Bristol Joint Directorate of Public Health UK and Visiting Lecturer London School of Hygiene and Tropical Medicineikeanya@doctors.org.uk

Learning objectives

To explore the definition of epidemiology

To introduce key concepts in epidemiology

To introduce the concepts of risk, risk measurement and standardization in epidemiology

What is epidemiology?

The study of epidemics?

The study of diseases?

The study of diseases of the skin?

Something scientists and academics use to confuse other people?

Definition of epidemiology

“The study of the distribution and determinants of health related states or events in

specified populations and the application of this study to control health problems”

- James Last A Dictionary of Epidemiology

Unpacking that definition

Study: Observing,recording,experimenting Distribution : Who, where, when Determinants: Why? Health related states Specified populations Application

Epidemiology asks or uses:

Person- Who?

Place- Where?

Time- When?

Helps us to understand: Why?

Specified populations

How many people in this room are infected with the HIV virus?

How many people in Toronto are infected ?

How many people in Canada are infected?

Why is it important to specify the population

In order to be able to compare between two populations, we need to know what the defined population is

For example,if we say 50 people in this room have an infection compared with 100 people in the next room, does it mean that infections are less common in this room?

Numerators and denominators

(N/d)

Numerator – the top half of the fraction

Denominator- the bottom number in the fraction

Numerators and denominators 2

There may be fewer people in this room than in the next room

Let’s assume that there are 100 people in this room and 1000 people in the next room

So 50 people with infections out of 100 people in this room means half (50/100) of the people in this room have infections

100 people with infections out of a 1000 in the next room means only a tenth (100/1000) of the next room have colds

Measuring disease frequency

There are 2 main measures used

Prevalence

Incidence

Prevalence and incidence

Prevalence - the number of people with a particular condition, habit at a specified time within a defined population eg prevalence of colds,smoking

Incidence - the number of NEW cases of a condition/habit in a defined population over a specified period of time

Distinguishing between incidence and prevalence

Prevalence includes both old and new cases and is usually expressed as a percentage

Incidence includes only NEW cases and is expressed as the number of cases per population per year

Time period and population must be specified

Prevalence

Prevalence of colds in this class Number of cases (people with colds) = 3 Population of class = 30 Prevalence = 3/30 Expressed as a percentage = 3/30 X 100 =10%

Incidence

Number of cases of newly diagnosed HIV infection in a city in 2003 is 900

Population of the city is 100 000

Incidence of HIV is 900 per 100 000 in 2003

Defining risk

Probability that an event will occur

Different from causation

Chance that if exposed to certain risk factors will develop condition

Risk and risk factors

Risk factors are factors that increase the probability that a disease will occur

Risk factors could be environmental behavioural/lifestyle genetic

Differentiating between risk and causation

Risk is about probability or likelihood

Causation is about “certainty”

Identifying a risk may be the first step to understanding causation eg smoking and lung cancer

Types of risk

Absolute risk

Relative risk

Attributable risk

Measures of risk – absolute risk

Number of cases in a defined population

Similar to incidence

If 100 people are infected with HIV in a town of 1000 people, the absolute risk of HIV in the town is 100 per 1000

But the people in the town have different lifestyles, genes,living conditions which absolute risk does not take note of

Measures of risk – relative risk

Going back to our example, we could divide the population of the town into injecting drug users (IDUs) and non-injecting drug users non-IDUs)

Count the number of cases of HIV in IDUs and count the number in non-IDUs

Relative risk (risk ratio) is the ratio between the two I.e.Risk in the exposed /risk in the unexposed

Relative risk

In our example, there were 400 IDUs in the town, and 80 of them were diagnosed with HIV in the year of our study. The risk of HIV in IDUs was therefore 80/400 = 0.2

There were 20 diagnoses of HIV in the non-IDU population of 600, so the risk of HIV in non-IDUs was 20/600 = 0.033

The relative risk is therefore 0.2 divided by 0.033=6.06

What does the relative risk mean?

From the example, we obtained a relative risk of 6.06

In simple terms it means that IDUs in the town in that year were 6.06 times more likely to be diagnosed with HIV than non-IDUs

Attributable risk

Difference between risk in the exposed and risk in the unexposed

Risk in exposed minus risk in unexposed From our example the attributable risk for

smokers in the town was 0.2-0.033=0.167

Rates

Rates are another means of expressing measurement

3 broad types of rates commonly used in epidemiology

Crude rates Specific rates Standardized rates

Crude rates

Looking at the death records in Newtown which has a population of 100 000 we find that 500 people died in 2005

In neighbouring OldTown with the same population of 100 000, there were 800 deaths in 2005

Comparing crude rates

Newtown had a crude death rate of 500 per 100 000

Oldtown had a crude death rate of 800 per 100 000

Oldtown appears to have a higher death rate than Newtown, but do the crude rates tell the whole story?

Newtown Oldtown

Age group Number of deaths

10-20 200 30

20-30 150 20

30-40 50 40

40-50 20 20

50-60 15 90

60-70 10 15070-80 20 250

80-90 35 200TOTAL 500 800

Delving deeper – specific rates

Looking at the number of deaths in different age groups we get a different picture

The majority of deaths in Oldtown occurred in people over the age of 60

The majority of deaths in Newtown occurred in people under the age of 40

Specific rates

Specific rates give us more detail by looking at the occurrence of events in a subgroup of the population

In the example, we used age groups, but could have used gender, ethnicity,occupation,etc

Comparing rates - standardisation

Going back to the example, we know that there were different patterns in the deaths recorded in the two towns

But we may find it difficult to compare rates between the two towns

Why?

Why standardize ?

Perhaps Oldtown is a retirement town with many old people and few young people?

Perhaps Newtown has very few old people and is a barracks town consisting largely of soldiers going to Iraq?

To enable valid comparison, we need to be comparing like with like – hence standardization

What are standardized rates?

Standardized rates are rates that take into account the structure of the population and adjust for differences in population structure

Rates can be age-standardized, sex-standardized, etc

Summary

Epidemiology uses person, time and place to study how illness and health are distributed in populations

In epidemiology, specifying populations and time periods is important

When interpreting epidemiology, always check that like is being compared with like