measures of disease burden
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Measures of Disease Burden
Dr. Ranadip Chowdhury M.D.Study Coordinator
CHRD-SAS
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Epidemiological Outcomes• Ratio: Relationship between two numbers
– Example: males/females
• Proportion: A ratio where the numerator is included in the denominator
– Example: males/total births
• Rate: A proportion with the specification of time
– Example: (Pneumonia cases in 2013/ total U-5 population in 2013) x 1,000
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In epidemiology, the occurrence of a disease or condition can be measured using rates and proportions. We use these measures to express the extent of these outcomes in a community or other population.
Rates tell us how fast the disease is occurring in a population.
Proportions tell us what fraction of the population is affected.
(Gordis, 2000)04/10/23 05:52 3
Concept of Risk
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Risk Versus Rate
Risk and rate are often used
interchangeably by epidemiologists but
there are differences
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Risk Versus Rate (cont.)
• 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
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Risk Versus Rate (cont.)
• 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
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The Three Elements in Measures of Disease Incidence
• E = an event = a disease diagnosis
• N = number of persons in the population in which the events are observed
• T = time period during which the events are observed
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Morbidity Measures
• Incidence is always calculated for a given period of time
• An attack rate is an incidence rate calculated for a specific disease for a limited period of time during an epidemic
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Population at risk (PAR)
• The denominator for incidence is the population at risk
• Not including– Existing cases– Individuals who are not capable of developing
the disease.
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Factors affecting population at risk
• Populations are dynamic– births and deaths (with different risk)– immigration, emigration and other losses
• Affected by immunity status• Removal from at-risk population
– Cases– Lost to follow up– Death due to other causes (competing risks)– Change in risk status (hysterectomy and uterine
cancer)
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Calculating population at risk
• Exact – Sum each person’s contribution to
time-at-risk– Must know exact times of entry,
disease onset, or withdrawal for every individuals
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Calculating population at risk
Mid-point population– Assume onset/withdrawal random over
time – Use population at the mid-point of study to
estimate average PAR (most recent census figure)
– Mean of start and end populations
Incidence Density
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Concept of person-years
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c
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rates: year 1 = 3/7.083 = 42.4/100 person-years year 2 = 3/2.50 =120/100 person-years both yrs 6/9.583 = 62.6/100 person-years
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Dealing with recurrent cases
• Count only first event– remove case from PAR
• Count all events– don’t remove case from PAR
• Count secondary etc. events only after biologically based recovery period– remove temporarily from PAR
• Count all events - stratify – Remove case from PAR for primary case– enter case in PAR for secondary case
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Morbidity Measures
• Prevalence is not a rate
• Point prevalence measures the frequency of all current events (old and new) at a given instant in time
• Period prevalence measures the frequency of all current events (old and new) for a prescribed period of time
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Illustration of several concept of morbidity
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Calculation of incidence density
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Relationship Between Prevalence and Incidence
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Factors Influencing Prevalence
Increased by:• Longer duration of the
disease• Prolongation of life of
patients without cure
• Increase in new cases• (increase in incidence)
• In-migration of cases
• Out-migration of healthy people
• In-migration of susceptible people
• Improved diagnostic facilities
• (better reporting)
Decreased by:•Shorter duration of
disease
•High case-fatality rate from disease
•Decrease in new cases (decrease in
incidence)
•In-migration of healthy people
•Out-migration of cases
• Improved cure rate of cases
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Relation of incidence and prevalence
• Prevalence depends on incidence
• Higher incidence leads to higher prevalence if duration of cases does not change.
• Limitation of the bathtub analogy – flow rate needs to be expressed relative to the size of the source
• Introducing a new analogy . . .
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Population at risk
Existing cases
Deaths, cures, etc.
Relationship Between Incidence and Prevalence (cont.)
• Diarrhea– Incidence High– Duration short– Prevalence low
• Tuberculosis– Incidence low– Duration long– Prevalence high
• Pneumonia– Incidence high– Duration short– Prevalence low
• Malaria– Incidence high– Duration medium-
long– Prevalence low-
medium04/10/23 05:52 29
Prevalence v/s incidence Point prevalence Period
prevalenceCumulative Incidence
Incidence Density
Numerator Existing cases(old and new)
Existing and new cases
New cases New cases
Denominator Initial Pop. Mid-point Pop.
Initial orMidyear Pop.
Person-time
Time One point A period A period A period
Unit None None None No./PT
Type proportion proportion proportion rate
Example question
Do you currently have asthma?
Have you had asthma during the last year?
Have you ever had asthma last year?
Study types Cross-sectional studiessurveillance
closedCohort studies
Open Cohort studies
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Calculation Practice
Skin Cancer on Sunny Beach:
1. Point prevalence on 9/9/20132. Period prevalence for year 20133. Incidence rate for year 2013
What information will you need?
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Diagnosed cases of Skin Cancer on Sunny Beach, 9/9/2013
Point Prevalence (9/9/2013)
= (10/450)*1000
= 22 per 1000
# of existing cases = 10
Total population at risk = 450
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Diagnosed cases of Skin Cancer on Sunny Beach, 2013
Average population at risk = 500
Incidence rate (year 2013)
= (5/500)*1000
= 10 per 1000
Period prevalence (year 2013)
= (15/500)*1000
= 30 per 1000
# of new cases = 5
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THANK YOU….
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