Epidemiological
terminology and measures
Preben Aavitsland
Contents
• Epidemiology
• Epidemiological measures
• Research questions
• Design
• Synthesis:
question  design  measure
Definitions of epidemiology
• “Epidemiology is the systematic search of causes
of disease”
• “Epidemiology is the science of occurrence and
determinants of health conditions and disease in
populations and use of this knowledge to control
health problems”
• “Epidemiology is the sicence of disease in
populations and factors that determine disease
occurrence”
• “Epidemiology is the science of disease
occurrence”
Research question
Design
Measure
Measure
(= what we measure)
The measures
• Measures of disease occurrence
– Prevalence
P
– Risk
R
– Incidence rate
I
• Measures of causal effects
– Risk difference
RD
– Risk ratio
RR
– Incidence rate difference
IRD
– Incidence rate ratio
IRR
– Odds ratio
OR
Measures of disease occurence
• Prevalence P
• Risk CI
- ”a snapshot photo”
- ”a photo with long exposure time”
(~cumulative incidence, incidence proportion, attack rate)
– Case fatality CFR = risk of death
• Incidence rate I
- ”a film”
(~incidence density)
– Mortality M = incidence of death
Prevalence (P) – 1
(Prevalence proportion)
The proportion of a population with a certain disease at
a given point in time
The probability that a randomly chosen individual has
the disease
P = number of diseased people at the point in time
number of individuals in the population
P = 0 to 1, or percentage, per million etc.
Prevalence (P) - 2
Point prevalence is prevalence at a certain point in
time, the true prevalence. The point is either a
calendar point in time, or a certain event, such
as birth.
Lifetime prevalence is the proportion who has had
the characteristic (the disease) during their
lifetime.
Seroprevalence is the proportion who has
antibodies, marking earlier or current infection,
i.e. a lifetime prevalence of the infection.
Calculating prevalence
16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 1
A
B
C
D
E
F
P = 2 / 4 = 0,5 = 50%
Risk (R) - 1
(Incidence proportion, cumulative incidence,
attack rate)
The proportion of the population who gets the
disease during a given time period
The risk that a randomly chosen individual will get the
disease during the time period
R = number of new cases during the time period
number of individuals in the population
R = 0 to 1, or percent, per million etc., but the
period must be stated
Calculating risk
Admission day
7 days later
A
B
x
C
x
D
E
Condition: Same follow up for all
R = 2 / 5 = 0.4 = 40%
Attack rate (AR)
• Risk during an outbreak
Usually expressed for the entire epidemic period,
from the first to the last case
Ex: Outbreak of cholera in country X
in March 1999
– Number of cases = 490
– Population at risk = 18,600
– Attack rate = 2.6%
Case-fatality (CFR)
The proportion of people with a disease who dies
from that disease during a time period that
usually corresponds to the duration of the
disease. Used for acute diseases. The
cumulative incidence of deaths.
The risk of dying from a disease in a time period (the
duration of the disease)
CFR =
number of deaths from the disease
number of people with the disease
CFR = 0 to 1, or percent, per million etc., but the
period must be stated
Problem with risk
• Must decide on time period
• Ideal: follow everyone for same time period
• Problem with long time periods
– Deaths to other causes
– Loss to follow up
• Example: Five year risk of HIV infection among
drug users
• Solution: Incidence rate
Incidence rate (I) – 1
(incidence density)
The speed of new cases of a disease in the
population
I=
number of new cases in the time period
sum of risk period for all individuals
I = number per time unit of risk, e.g. per person
year
Incidence rate (I) - 2
The numerator is the number of new cases in a time
period
The denominator is person time at risk
-
either the size of the population in the middle of
the period (usually acceptable)
-
or the sum of the calculated time at risk for all
the persons in the population
Calculating incidence rate
16 17 18 19 20 21 22 23 24 25 26
Days at risk
6.0
A
x
B
6.0
C
10.0
D
8.5
E
Total days at risk
x
5.0
35.5
I = 2 / 35.5 persondays = 5,6 / 100 persondays
Mortality rate (M)
The speed of new deaths caused by this disease in the
population, i.e. the incidence of death
M = number of new deaths of the disease in the period
sum of risk period for all individuals
M = number per time unit of risk, e.g. per person year
Risk versus incidence rate
Risk R
Incidence rate I
Synonyms
(incidence proportion,
cumulative incidence,
attack rate)
(incidence density)
Smallest
value
0 (or 0%)
0
Greatest
value
1 (or 100%)
∞
Units
None
/ person-time
Measures of causal effects
•
•
•
•
Risk difference RR
Risk ratio RR
Incidence rate difference IRD
Incidence rate ratio IRR
• Odds ratio OR
The cohort study
exposed
unexposed
The cohort study
exposed
Occurrence among
exposed (I1 or R1)
unexposed
Occurrence among
unexposed (I0 or R0)
Absolute measures of causal effects
• Exposed group:
• Unexposed group:
• Risk difference
R1
R0
RD
= 0.67
= 0.24
= R1 – R0
= 0.67 – 0.24 = 0.43
• Exposed group:
• Unexposed group:
• Incidence rate diff.
I1
I0
IRD
= 172/100 000 person-years
= 12/100 000 peron-years
= I1 – I0
= 172/100 000 – 12/100 000
= 160/100 000 person-years
Relative measures of causal effects
• Exposed group:
• Unexposed group:
• Risk ratio
R1
R0
RR
= 0.67
= 0.24
= R1 / R0
= 0.67 / 0.24 = 2.8
• Exposed group:
• Unexposed group:
• Incidence rate ratio
I1
I0
IRR
= 172/100 000 person-years
= 12/100 000 peron-years
= I1 / I0
= 172/100 000 / 12/100 000
= 14.3
Absolute or relative measures
Bank A
• Start with € 100
• Invest in one year
• Ends with € 140
Bank B
• Start with € 1000
• Invest in one year
• Ends with € 1150
• Absolute gain
140€ – 100€ = 40€
• Absolute gain
1150€ - 1000€ = 150€
• Relative gain
140€ / 100€ = 1.40
• Relative gain
1150€ / 1000€ = 1.15
Odds ratio (OR)
• Term for RR or IRR when measured in a
case-control study
• … more to follow
Classes of research questions
1 How many are (becoming) diseased? (occurrence)
2 Why are some diseased? (causal effects, etiology)
3 How can we tell whether someone is diseased?
(diagnostics)
4 What can we do for the diseased? (intervention effects)
5 How does the diseased fare? (prognosis)
6 How does it feel to have the disease? (patient
experiences)
Example: HIV infection among drug users
1 What is the incidence rate of HIV among drugu users? (occurrence)
2 How much does needle sharing increase the incidence rate of HIV?
(causal effects, etiology)
3 How good is the saliva test in diagnosing HIV? (diagnostics)
4 How much does needle distribution decrease the incidence rate of
HIV? (intervention effects)
5 How long do drug users with HIV live? (prognosis)
6 How does it feel to be a drug user with HIV infection? (patient
experiences)
Objective
• The objective of an epidemiological study
is to obtain an estimate of an
epidemiological measure without random
or systematic error.
• The research question should state what
we want to measure.
Make specific questions
Unspecific
question:
Specific question:
”We wish to focus closer
needle sharing
at the problem of drug
increase the risk
users acquiring HIV
among drug users of
through sharing needles
becoming HIV
for injections.”
infected?”
”By how much does
 Points to RR
Designs
•
•
•
•
•
Trial
Cohort study
Case-control study
Cross-sectional study
Qualitative study
Question  Design Measure
Trial
1 Occurrence
2 Causal effect
Cohort
Case-
Cross-
Qualitative
study
control
sectional
study
study
study
I, R
RD, RR, IRD, IRR OR (~RR, IRR)
3 Diagnostics
P
(RR, RD)
Sens, Spec
4 Intervention effects RRR, ARR
5 Prognosis
6 Experiences
CFR, M
P
Text
Summary
• Epidemiological research is to measure
- occurrence (I, R, P) or
- causal effects (RD, RR, IRD, IRR)
• Make a clear research question:
What do you want to measure?
• The research question determines the
design