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Learning Objectives (cont.): 7.Understand special types of incidence and prevalence measures. 8.Understand the interrelationship between incidence, prevalence, and duration of disease. 9.Differentiate the use of incidence and prevalence measures.
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Measures of Disease Occurrence
Dr. Kamran Yazdani, MD MPHDepartment of Epidemiology & Biostatistics
School of public healthTehran University of Medical Sciences
Learning Objectives:
1. Understand ratios, proportions, and rates.2. Define, calculate, and interpret incidence.3. Understand the use of person-time
denominators.4. Distinguish between cumulative incidence
and incidence rate.5. Define, calculate, and interpret prevalence.6. Distinguish between point and period
prevalence.
Learning Objectives (cont.):
7. Understand special types of incidence and prevalence measures.
8. Understand the interrelationship between incidence, prevalence, and duration of disease.
9. Differentiate the use of incidence and prevalence measures.
The study of the distribution and determinants of health-related states and events in specified populations
and The application of this study to control of
health problems
Definition of Epidemiology
Disease distributionDescriptive Studies
Disease determinantsAnalytic Studies
Two essential components
These main tools in epidemiology are:
Measuring Tools for Describing Categorical Outcomes
• Ratio• Proportion• Rate
= 5 / 2 = 2.5 / 1
• The quotient of 2 numbers• Numerator NOT necessarily INCLUDED in the
denominator• Allows to compare quantities of different nature
Ratio
Ratio, Examples # beds per doctor
– 850 beds/10 doctors– R = 85 beds for 1 doctor
# participants per facilitator # inhabitants per latrine
Sex ratio: Male / Female Female / Male
Odds ratio Rate ratio Prevalence ratio
2--- = 0.5 = 50% 4
Proportion• The ratio of 2 numbers• Numerator NECESSARELY INCLUDED
in the denominator• Quantities have to be of same nature• Proportion always ranges between 0 and 1 • Percentage = proportion x 100
Proportion, Examples
Proportion of Myopia in a survey sample:
– 5600 samples, 168 myopic patients
– Proportion of myopics = 168/5600 = 0.03
– Percentage of myopics = 3%
Indicates the magnitude of a part, related to the total.
In epidemiology, tells us the fraction of the population that is affected.
Numerical value of a proportion: 0 to 1.0
Linked to probability theory (i.e. risk of developing disease)
For ease of usage, can multiply a proportion by 100 to get a percentage
Example: p = 0.03 = 3%
Proportions
A proportion in which TIME forms part of the denominator
Speed of occurrence of an event over time
Numerator - number EVENTS observed for a given time
Denominator- population in which the events occur
includes time
Rates
Epidemiologic rates contain the following elements:
• disease frequency (in the numerator)• unit size of population• time period during which an event
occurs
Rates
Calculate crude annual death rate in the US:
Crude death rate =(Annual death count / Reference population (during midpoint of year))
x 1,000
Death count in U.S. during 1990:2,148,463U.S. population on June 30, 1990: 248,709,873
2,148,463Crude death rate = ----------------- x 1,000 = 8.64 / 1,000 / year
248,709,873
Rates – Example
Discussion QuestionDiscussion Question
What does a crude annual death rate of8.64 per 1,000 per year mean?
Measures of Disease OcurrenceMeasures of Disease Ocurrence(frequency)(frequency)
IncidenceHow fast are new cases occurring?
PrevalenceHow much disease is present now?
Incidence
The development of new cases of a disease that occur during a specified period of time in previously disease-free or condition-free (“at risk”) individuals.
Incidence Incidence quantifies the “development” of disease --- Most fundamental measure of
disease frequency and leads to the development of the concept of risk (i.e transition from non-diseased to diseased state)
- Cumulative incidence (CI)(“Incidence proportion”)
- Incidence rate (IR)(“Incidence density”)
Cumulative Incidence (CI)PROPORTION of individuals who become diseased during a specified period of time(e.g. all new cases during 1998)
Range: 0 to 1.0
Also referred to as “incidence proportion.”
Cumulative Incidence (CI)
No. of new cases of disease during a given periodCI = --------------------------------------------------------------
Total population at risk during the given period
Example: During a 1-year period, 10 out of 100 “at risk” persons develop the disease of interest.
10CI = ----- = 0.10 or 10.0%
100
Cumulative Incidence (CI)
To accurately calculate cumulative incidence, we need to follow the entire population for the specified time interval. Often times, this does not fully occur.
Cumulative incidence provides an estimate of the probability (risk) that an individual will develop a disease during a specified period of time.
Cumulative Incidence (CI) Keep in mind that over any appreciable
period of time, it is usually technically impossible to measure risk.
This is because if a population is followed over a period of time, some people in the population will die from causes other than the outcome under study
The phenomenon of being removed from a study through death from other causes is referred to as ”competing risks”.
Cumulative Incidence (CI) When the follow-up of patients is
incomplete, we have to use the survival analysis methods:
– Life Table
– Kaplan-Meier
Cumulative Incidence Incidence proportion
Risk
CI assumes that entire population at risk followed up for specified time period
xxx
x
x
x
xx disease onset
Month 1 Month12
CI = 7/12 per year
= 0.58 per year
Incidence Rate (IR)No. new cases of disease during a given period
IR = -----------------------------------------------------------Total “person-time” of observation
Range = 0 to Infinity
Since the number of cases is divided by a measure of time of observation, rather than people, this helps address the problem of competing risks.
Incidence Rate (IR)
When we observe a group of individuals for a period of time in order to ascertain the DEVELOPMENT of an event….
- The actual time each individual is observed will most likely vary.
What is person time?
Discussion QuestionDiscussion Question
In a 2-year study of the development of disease X, why might the actual
time each individual is observed vary?
Discussion QuestionDiscussion Question
Because:• Subjects may be recruited at different times
• Subjects may emigrate
• Subjects may choose to leave study
• Subjects may die
• Subjects may get the disease we are
studying
Person-TimePerson Follow-up Time on Study Person Yrs.
1 <-------------------------------------> 2 2 <--------------------------------------D 2 3 <-----------------WD 1 4 <-------------------------------------------------------> 3 5 <-------------------------------------> 2
1995 1996 1997 1998 Jan. Jan. Jan. Jan.
Study Period: 3 YearsStudy Participants: 5Person Years of Observation: 10Average Duration of Follow-Up: 2.0 Years
No. new cases of disease during a given periodIR = ------------------------------------------------------------
Total “person-time” of observationSo,
1 caseIR = ----------- = 1 case per 10 P-Y follow-up
10 P-YWhereas,
1 caseCI = ------------ = 0.20 = 20.0%
5 persons
Incidence Rate (IR)
When we use individual data (cohort study):We use person-time as the denominator
Incidence Density
When we use aggregate data:We use the average population as the denominator
Incidence RateAssumptio: homogenous distribution of events and
losses (or additions)e.g.
Crude Death Rate
Incidence Rate (IR)
The IR of 1 case per 10 P-Y is equivalent to 0.2 cases per 2 years:which suggests a 20% risk of disease development within 2 years of follow-up.
Whereas, the CI risk estimate of 20% (1 case per 5 persons) was based on a period of 3 years of follow-up.
Comparison of IR and CI
Risk and rate are often used interchangeably by epidemiologists
but there are differences
Comparison of IR and CI
Risk is a probability statement assuming an individual is not removed for any other reason during a given period of time
As such, risk ranges from 0 to 1 (no chance to 100% probability of occurrence)
Risk requires a reference period and reflects the cumulative incidence of a disease over that period
Example: 1 in a million chance of developing cancer in a 70 year lifetime
Comparison of IR and CI
Rates can be used to estimate risk if the time period is short (annual) and the incidence of disease over the interval is relatively constant
If however, individuals are in a population for different periods of time for any reason, then you should estimate risk by incidence density
Comparison of IR and CI
Discussion QuestionDiscussion Question
Previously, we said that the incidence ratecan range from 0 to infinity!
How can this be?
Discussion QuestionDiscussion Question
Example100 subjects have been followed up for 2 month. 20 events have occurred during this time. What is the IR in P-Y?
Discussion QuestionDiscussion Question
Example100 subjects have been followed up for 2 month. 20 events have occurred during this time. What is the IR in P-Y?IR = (20/100) / 2 = 1 per 10 person-month
= 12 per 10 P-Y = 120%/yearTherefore, as time increases, IR approaches
infinity.
Incidence Rate (IR)
NOTE: The selection of the time unit for thedenominator is arbitrary, and is notdirectly interpretable:
Example: 100 cases / person yearcan also be expressed as:
10,000 cases / person century8.33 cases / person month1.92 cases / person week0.27 cases / person day
In general:Risk estimates derived from IR and CI calculations
will be similar when:• Follow-up loss is minimal• The disease of interest occurs infrequently.
CI is most useful if interest centers on the probability than an individual will become ill over a specified period of time.
IR is preferred if interest centers on how fast the new cases are occurring in the population.
Comparison of IR and CI
Measures of Prevalence Prevalence
– Point prevalence Do you have health condition now?
– Period prevalence Have you had health condition during past six
months?– Lifetime prevalence
Have you ever had health condition?
Importance of Prevalence Data
Burden of illness in population– Treatment needs– Burden on social services– Burden on individual well-being
“Point” PrevalenceThe usual prevalence
Number of existing casesP = --------------------------------
Total population
At a set point in time (i.e. September 30, 1999)
“Point” Prevalence
Example:On June 30, 1999, neighborhood A has:
• population of 1,600• 29 current cases of hepatitis B
So, P = 29 / 1600 = 0.018 or 1.8%
“Period” Prevalence Number of existing cases
Pp = -------------------------------- Total population
During a time period (i.e. May 1 - July 31, 1999)Includes existing cases on May 1, and
thosenewly diagnosed until July 31.
“Period” PrevalenceExample:Between June 30 and August 30, 1999,
neighborhood A has:• average population of 1,600• 29 existing cases of hepatitis B on June 30• 6 incident (new) cases of hepatitis B
between July 1 and August 30
So, Pp = (29 + 6) / 1600 = 0.022 or 2.2%
“lifetime” Prevalence Number of existing cases
LP = -------------------------------- Total population
During any time in the past
Prevalence
In general, a person’s probability of being captured as a prevalent case is proportional to the duration of his or her disease.
Thus, a set of prevalent cases tends to be skewed toward cases with more chronic forms of the disease.
Discussion QuestionDiscussion Question
How are incidence andprevalence of disease related?
Discussion QuestionDiscussion Question
Prevalence depends on:
- Incidence rate
- Disease duration
House Guests Example
Relationship between prevalence and incidenceRelationship between prevalence and incidence
WHEN (the steady state is in effect):
a) Incidence rate (I) has been constant over time
b) The duration of disease (D) has been constant over time:
ID = P / (1 – P)
P = ID / (1 + ID)
c) If the prevalence of disease is low
(i.e. < 0.10 or 0.05): P = ID
Relationship between prevalence and incidenceRelationship between prevalence and incidence
Relationship between prevalence and incidenceRelationship between prevalence and incidence
High prevalence may reflect: High risk Prolonged survival without cure
Low prevalence may reflect: Low risk Rapid fatal disease progression Rapid cure
Examples: Ebola, Common cold
Relationship between prevalence and incidenceRelationship between prevalence and incidence
Cancer of the pancreas– Incidence low– Duration short– Prevalence low
Adult onset diabetes– Incidence low– Duration long– Prevalence high
Roseola infantum– Incidence high– Duration short– Prevalence low
Essential hypertension– Incidence high– Duration long– Prevalence high
Study design for Study design for Incidence & PrevalenceIncidence & Prevalence
Incidence (follow-up studies):- Cohort study- Clinical trial
Prevalence: - Cross-sectional- Case-Control (prevalent cases)
Uses of Incidence & Uses of Incidence & Prevalence MeasuresPrevalence Measures
Prevalence: Snap shot of disease or health event
Help health care providers plan to deliver services
Indicate groups of people who should be targeted for control measures
May signal etiologic relationships, but also reflects determinants of survival
Uses of Incidence & Uses of Incidence & Prevalence MeasuresPrevalence Measures
Incidence: Measure of choice to:--- Estimate risk of disease development--- Study etiological factors--- Evaluate primary prevention programs
Discussion QuestionDiscussion Question
Why is incidence preferred overprevalence when studying the
etiology of disease?
Because, in the formula: P = I x D
D is related to : - The subject’s constitution - Access to care
- Availability of treatment - Social support - The severity of disease
Discussion QuestionDiscussion Question
So prevalent cases reflect factors related to the incidence of disease (Etiological factors), AND factors related to the duration of disease (Prognostic factors)
Thus, they are not adequate for studies trying to elucidate Disease Etiology
Discussion QuestionDiscussion Question
PROBLEMS WITH INCIDENCE AND PROBLEMS WITH INCIDENCE AND PREVALENCE MEASURESPREVALENCE MEASURES
Problems with Numerators:
• Frequently, the diagnosis of cases is not straightforward
• Where to find the cases is not always straightforward
PROBLEMS WITH INCIDENCE AND PROBLEMS WITH INCIDENCE AND PREVALENCE MEASURESPREVALENCE MEASURES
Problems with Denominators:
• Classification of population subgroups may be ambiguous (i.e race/ethnicity)
• It is often difficult to identify and remove from the denominator persons not “at risk” of developing the disease.
Exercise
0123456789
10
Jan Feb Mar Apr May Jun Jul
Ratio males / female=? Prevalence March1 =?Proportion of women=? Prevalence March-July =?
Incidence Proportion March-July =?
Exercise
A
B
C
D
E
90 91 92 93 94 95 96 97 98 99 00 Time at risk
x
x
6.0
6.0
11.0
9.5
5.0
Total years at risk 37.5
-- time followedx disease onset ID = ?
What is the interpretation?