Epid 600 Class 3 Disease Occurence

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EPID 600; Class 3Measuring disease occurrence

University of Michigan School of Public Health

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Epidemiology and measurement

Measurement is centralto epidemiology

Fundamental observations in epidemiology are

measures of the occurrence of illness

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Quantification in epidemiology

1. Prevalence2. Risk (incidence proportion)3. Incidence rate4. Odds

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EXAMPLES

14 adult men per 1,000 were HIV + in Tanzania in June 1995

27 adult men per 1,000 were HIV+ in Tanzania in 1995

Prevalence =

Number of cases

Number of persons in

population

at a specified

time

Specified time interval can be a point or period of time

1. Prevalence (proportion)

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2. Risk (incidence proportion)

In epidemiology, risk applies to an individual and refers to the

probability that a person will develop a given disease

In epidemiology, risk is seldom measured at the individual level but

rather at the population level, hence, the risk measurement for agroup

is referred to as incidence proportion

Risk = Number of new cases of diseaseNumber of persons followed

over a

time

period

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Example, risk

Fixed population: 1000 people observed for 5 years

When people become ill, assume all become ill on the last day of the time period

0.5 years 3 sick 1.0 years 5 sick





967 people never became ill

Therefore, Risk = # sick/total pop = 33/1000=0.0336


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Risk, examples

Voluntary risks Risk of death per person per year

Motorcycling 1 in 50

Smoking a pack a day 1 in 200

Taking contraceptive pills 1 in 5,000Legal abortion, >12 weeks 1 in 5,900

Drinking 1 bottle of wine/day 1 in 13,300

Playing soccer 1 in 25,500

Canoeing 1 in 100,000

Skiing 1 in 430,000

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Different risk patterns over time

Morbidity A Morbidity B

Age

Annualr

iskofmorbidity

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Two key notions in stating and

interpreting risk

Risk is meaningless without a time interval

e.g., Risk of death from cardiovascular disease among

women 60 years of age is 2%...means what?

Competing risks make it difficult to use risk as the only

assessment of disease occurrence in a study although this

can be done in studies where follow-up is short and

competing risks are low; e.g., Salk vaccine trial in children

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Incidence rate

EXAMPLE

20 new cases of HIV infection during 8,000,000 person

years of follow-up, that is, among 8,000,000 persons

followed-up for 1 year

Incidence Rate =

Number of new cases

Total time at risk of persons followed

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Understanding person-time

T1 T2 T3 T4 T5 T6 T7 T8 T9 T10 T11 T12 T13 T14 T15 T16 T17 T18 T19 T20 TT

P1

P2

P3

P4

P5

P6

P7

P8

P9

P10

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A person-time example


P1 14

P2 20

P3 11

P4 11

P5 20

P6 20

P7 10

P8 20

P9 2

P10 10

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An example


P1 14

P2 20

P3 11

P4 11

P5 20

P6 20

P7 10

P8 20

P9 2

P10 10

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Therefore

Prevalence at T11=1

7

Risk=3

10new cases over a given time period

Incidence rate =3

14 + 20 +11+11+ 20 + 20 +10 + 20 + 2 +10=

3new cases

138 person time

Assume lightning bolt is disease onset

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Example, Incidence Rate

Fixed population: 1000 people observed for 5 years

When people become ill, assume all become ill on the last day of the time period






967 people never became ill

Therefore, IR= # sick/PYO = 33/[(967*5)+(3*0.5)+...etc]=33/4,921=6.7/1000 PYOs

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Another way to think of incidence and

prevalence

Incidence

Prevalence

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prevalence

Incidence

Prevalence

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prevalence

Incidence

Prevalence

factors affecting prevalence include

incidence, duration of disease,

death rates

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Factors leading to increased prevalence

Increased incidence rate

Increased duration of disease, e.g., prolonged

survival

More case finding, e.g., screening

Lower mortality

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HIV Prevalence and Incidence

Comparing incidence and prevalence

time

numberofcas

esper100,0

00population

numberofnew

casesper100,0

00

population

peryear

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Notes about prevalence and incidence

Prevalence represents the number of cases among persons of interest

at a given point in time

Therefore, prevalence is not a rate; the term prevalence rate should

not exist

Incidence (including both incidence proportion and incidence rate)

represents number ofnewcases over a particular person-time of

follow-up

Therefore risk (incidence proportion) and incidence rate both are not

meaningful without a time unit

Always be as specific as possible when articulating units of

measurement...what are you measuring? among who? over what timeperiod?

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Risk and prevalence range from 0 to 1 Incidence rate ranges from 0 to infinity

Comparing prevalence, risk (incidence

proportion), and incidence rates

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Think of numerator and denominator

How do we know something is a case?

How do we count population at risk?What is a specific time period?

Issues in measurement of incidence and

prevalence

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Interrelations among measures (1),

incidence proportion and incidence rate

Risk = Incidence rate x time

[0-1] [0-] [0-]

This is only applicable where risk is low (


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Example, incidence proportions and rates

Population of 1,000 persons

Mortality rate of 11 deaths per 1000 person years over a 20

year time period

Therefore, Risk = [11/1000]*20 year = 0.22So, risk is that among 1000 people there would be 220

deaths (22%) over the 20 years

This ignores population change or possible addition or

removal of population from follow-up

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Interrelations among measures (2),

prevalence and incidence rate

IR * D = P

1 P

This applies only in steady state, where incidence rates

and disease duration are stable over time

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And....

*1

( * ) * (1 )

* * *

* * *

(1 * ) **

1 *

P IR D

P

therefore

P IR D P

P IR D IR D P

P IR D P IR D

P IR D IR D IR D

P IR D

=

=

=

+ =

+ =

=

+

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Therefore, prevalence and incidence

rate

IR * D = P

1 P

Therefore, for low prevalence (and steady state),

IR * D P

if p


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4. Odds

1podds

p

=

probability, risk

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Interpreting odds

Odds = p/(1-p)

Therefore, if probability is 0.75, odds are

0.75/(1-0.75)=0.75/0.25=3

Note that 3:1 odds means that a horse has a 75%probability oflosinga race

Good odds, if this is a horse race, are 1:1, that is,

probability is 0.50 and odds are 0.50/(1-0.50)=1; this then

means that a horse has a 50:50 chance ofwinning or losing

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=# of deaths in 1 year

# of persons in population

at mid-year

x 1000Annualmortality

rate

Annual mortality rate

Notes

Multiplication by 1000 is by convention32


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=total # of deaths

# of persons with a diseasex 1000

Case

fatality

rate

Case fatality rate

Notes

Multiplication by 1000 is by convention The time period here is implicit as the time for persons with disease, presumably

low

For diseases with low fatality, survival measures are better used 33


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=

total # of new persons with disease

# of persons at risk of disease

x 100Attackrate

Attack rate

Note: the time period here is implicit as the time for persons withdisease, presumably low

For diseases with low fatality, survival measures are better used34


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Some examples

Is the prevalence of osteoarthritis in the population low or high?

Is the annual mortality rate from osteoarthritis low or high?

Is the annual mortality rate from respiratory anthrax low or high?

Is the case fatality rate from respiratory anthrax low or high?

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Measuring Tuberculosis

Recap...some reasons why accurate measurement is

important

To define public health needs

To assess how well we are doing at addressing those needsA review of measurement issues in the context of the global

TB burden was published in the Lancet in April 2008

Dye et al. Lancet. Measuring tuberculosis burden, trends, and the impact of control programmes. 2008; 8: 233-243.

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Measuring Tuberculosis trends


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incidence

over time by

country



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Prevalence estimates


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Problems: Plausibility of measured distribution

Cases/suspects

Fluctuations in reported cases


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Problems: Plausibility of measured distribution

Cases/suspects

Annual fluctuations in reported cases


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Final notes (1), expressing prevalence

and incidence

Prevalence often expressed as cases per 100,000

Incidence rate is also sometimes expressed as per 100,000

but this is wrong since needs time dimension (per year?)

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Summary of measures of disease

frequency

Prevalence Risk Incidence rate Odds

NumeratorNumber with

disease

Number with

new disease

Number with

new disease

Risk

DenominatorTotal number

of people

Total number

of people at

risk at

baseline

Person years

at risk1-Risk

TimeAt a point in

time

Over a time

interval

Over a time

interval

Over a time

interval

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Epid 600 Class 3 Disease Occurence