1.
DescriptiveDescriptive
epidemiologyepidemiology
Dr. KANUPRIYA CHATURVEDIDr. KANUPRIYA CHATURVEDI
2.
How we view the world…..How we view the world…..
Pessimist:Pessimist: The glass isThe glass is
half empty.half empty.
OptimistOptimist: The glass is: The glass is
half full.half full.
EpidemiologistEpidemiologist: As: As
compared to what?compared to what?
4.
Epidemiology is...
"The worst taught course in Medical
school."
Medical Student
5.
Epidemiology is...
"The science of making the obvious
obscure."
Clinical Professor
6.
Epidemiology is...
"The science of long division....
I'=[(480)(log2)(10E6)]/[(9.1)(0.955po)
+0.45n]"
Statistician
7.
Definition of Epidemiology*
"The STUDY of the DISTRIBUTION and
DETERMINANTS of HEALTH-
RELATED STATES in specified
POPULATIONS, and the application of this
study to CONTROL of health problems."
*Last, J.M. 1988. A Dictionary of Epidemiology, 2nd ed.
8.
Epidemiology: DefinitionEpidemiology: Definition
Dynamic study of the
Determinants
Occurrence
Distribution
Control
Pattern
Of health and disease in a population
9.
EpidemiologyEpidemiology
EPI DEMO LOGOS
Upon,on,befall People,population,man the Study of
The study of anything that happens to
people
“That which befalls man”
10.
Definition of Epidemiology
A quantitative basic science, built on a working
knowledge of probability, statistics and sound
research methods.
A method of causal reasoning, based on
developing and testing biologically plausible
hypothesis pertaining to occurrence and
prevention of morbidity and mortality.
A tool for public health action to promote and
protect the public's health based on science, causal
reasoning, and a dose of practical common sense.
11.
Epidemiology is a QuantitativeEpidemiology is a Quantitative
DisciplineDiscipline
Measures of frequencyMeasures of frequency
Counts and ratesCounts and rates
Measures of associationMeasures of association
Relative riskRelative risk
Odds ratioOdds ratio
Statistical inferenceStatistical inference
P-valueP-value
Confidence limitsConfidence limits
13.
EpidemiologyEpidemiology
DescribesDescribes
health eventshealth events
cause and risk factors of diseasecause and risk factors of disease
clinical pattern of diseaseclinical pattern of disease
Identify syndromesIdentify syndromes
Identify control and/or preventive measuresIdentify control and/or preventive measures
14.
So, EpidemiologySo, Epidemiology
Is theIs the basic sciencebasic science of public healthof public health
Provides insight regarding theProvides insight regarding the naturenature,, causescauses,,
andand extentextent of health and diseaseof health and disease
Provides information needed toProvides information needed to planplan andand targettarget
resourcesresources appropriatelyappropriately
15.
Kinds of EpidemiologyKinds of Epidemiology
DescriptiveDescriptive
AnalyticAnalytic
ExperimentalExperimental
Further studies to determine the
validity of a hypothesis concerning
the occurrence of disease.
Deliberate manipulation of the
cause is predictably followed
by an alteration in the effect
not due to chance
Study of the occurrence and
distribution of disease
16.
Overview of epidemiologic designOverview of epidemiologic design
strategiesstrategies
DescriptiveDescriptive
Populations{Correlational studies}Populations{Correlational studies}
IndividualIndividual
Case reportCase report
Case seriesCase series
Cross sectional studiesCross sectional studies
Analytic studiesAnalytic studies
ObservationalObservational
Case controlCase control
CohortCohort
RetrospectiveRetrospective
ProspectiveProspective
Interventional/ExperimentalInterventional/Experimental
Randomized controlled trialRandomized controlled trial
Field trialField trial
Clinical trialClinical trial
17.
Descriptive vs. Analytic EpidemiologyDescriptive vs. Analytic Epidemiology
DescriptiveDescriptive
Used when little isUsed when little is
known about theknown about the
diseasedisease
Rely on preexistingRely on preexisting
datadata
Who, where, whenWho, where, when
Illustrates potentialIllustrates potential
associationsassociations
AnalyticAnalytic
Used when insight aboutUsed when insight about
various aspects of disease isvarious aspects of disease is
availableavailable
Rely on development of newRely on development of new
datadata
WhyWhy
Evaluates the causality ofEvaluates the causality of
associationsassociations
Both are
18.
Descriptive StudiesDescriptive Studies
Relatively inexpensive and less time-consumingRelatively inexpensive and less time-consuming
than analytic studies, they describe,than analytic studies, they describe,
Patterns of disease occurrence, in terms of,Patterns of disease occurrence, in terms of,
Who gets sick and/or who does notWho gets sick and/or who does not
Where rates are highest and lowestWhere rates are highest and lowest
Temporal patterns of diseaseTemporal patterns of disease
Data provided are useful for,Data provided are useful for,
Public health administrators (for allocation of resources)Public health administrators (for allocation of resources)
Epidemiologists (first step in risk factor determination)Epidemiologists (first step in risk factor determination)
19.
Descriptive EpidemiologyDescriptive Epidemiology
Correlational studiesCorrelational studies
Case reportsCase reports
Case seriesCase series
Cross sectional studiesCross sectional studies
20.
Correlational Studies (Ecological Studies)Correlational Studies (Ecological Studies)
Uses measures that represent characteristics ofUses measures that represent characteristics of
entire populationsentire populations
It describes outcomes in relation to age, time,It describes outcomes in relation to age, time,
utilization of services, or exposuresutilization of services, or exposures
ADVANTAGESADVANTAGES
We can generate hypotheses for case-control studies andWe can generate hypotheses for case-control studies and
environmental studiesenvironmental studies
We can target high-risk populations, time-periods, orWe can target high-risk populations, time-periods, or
geographic regions for future studiesgeographic regions for future studies
21.
Correlational StudiesCorrelational Studies
LIMITATIONSLIMITATIONS
Because data are for groups, we cannot link disease andBecause data are for groups, we cannot link disease and
exposure in individualexposure in individual
We cannot control for potential confoundersWe cannot control for potential confounders
Data represent average exposures rather than individualData represent average exposures rather than individual
exposures, so we cannot determine a dose-responseexposures, so we cannot determine a dose-response
relationshiprelationship
Caution must be taken to avoid drawing inappropriateCaution must be taken to avoid drawing inappropriate
conclusions, orconclusions, or ecological fallacyecological fallacy
22.
Patterns of disease Occurrence :Patterns of disease Occurrence :
CorrelationCorrelation ofof PopulationPopulation statisticsstatistics
EcologicEcologic (( correlationcorrelation ) studies) studies
Used as first step in determining associationUsed as first step in determining association
plotplot :: disease (population) burden [ Y axis ]disease (population) burden [ Y axis ]
vs.vs. prevalence of “risk factor” [ X axis ]prevalence of “risk factor” [ X axis ]
e.g. smoking vs. lung cancere.g. smoking vs. lung cancer
-- correlation coefficient : r ; + 1 to -1-- correlation coefficient : r ; + 1 to -1
Quantifies linear relationship between exposure & diseaseQuantifies linear relationship between exposure & disease
23.
Case Reports (case series)Case Reports (case series)
Report of a single individual or a group ofReport of a single individual or a group of
individuals with the same diagnosisindividuals with the same diagnosis
AdvantagesAdvantages
We can aggregate cases from disparate sources to generateWe can aggregate cases from disparate sources to generate
hypotheses and describe new syndromeshypotheses and describe new syndromes
Example: hepatitis, AIDSExample: hepatitis, AIDS
LimitationsLimitations
We cannot test for statistical association because there is noWe cannot test for statistical association because there is no
relevant comparison grouprelevant comparison group
Based on individual exposure {may simply be coincidental}Based on individual exposure {may simply be coincidental}
24.
Case report/Case series(contd.)Case report/Case series(contd.)
ImportantImportant interfaceinterface between clinical medicine &between clinical medicine &
epidemiologyepidemiology
Most common type of studies published inMost common type of studies published in
medical journals{1/3medical journals{1/3rdrd
of all}of all}
e.g. Frisbee finger , break dancing necke.g. Frisbee finger , break dancing neck
AIDS ~ b/w oct1980-may81, 5 cases of P.cariniiAIDS ~ b/w oct1980-may81, 5 cases of P.carinii
pneumonia were diagnosed among previously healthypneumonia were diagnosed among previously healthy
young homosexual males in L.A.young homosexual males in L.A.
25.
Cross-Sectional Studies (prevalence studies)Cross-Sectional Studies (prevalence studies)
Measures disease and exposure simultaneously in aMeasures disease and exposure simultaneously in a
well-defined populationwell-defined population
AdvantagesAdvantages
They cut across the general population, not simply thoseThey cut across the general population, not simply those
seeking medical careseeking medical care
Good for identifying prevalence of common outcomes, suchGood for identifying prevalence of common outcomes, such
as arthritis, blood pressure or allergiesas arthritis, blood pressure or allergies
LimitationsLimitations
Cannot determine whether exposure preceded diseaseCannot determine whether exposure preceded disease
It considers prevalent rather than incident cases, resultsIt considers prevalent rather than incident cases, results
will be influenced by survival factorswill be influenced by survival factors
Remember: P = I x DRemember: P = I x D
26.
Cross-Sectional StudiesCross-Sectional Studies
Can be used as a type of analytic study for testingCan be used as a type of analytic study for testing
hypothesis, when;hypothesis, when;
Current values of exposure variables are unalterable overCurrent values of exposure variables are unalterable over
timetime
Represents value present at initiation of diseaseRepresents value present at initiation of disease
E.g. eye colour or blood groupE.g. eye colour or blood group
If risk factor is subject to alterations by disease, onlyIf risk factor is subject to alterations by disease, only
hypothesis formulation can be donehypothesis formulation can be done
27.
The epidemiologic approach:The epidemiologic approach:
Steps to public health actionSteps to public health action
MEASURES
Counts
Times
Rates
Risks/Odds
Prevalence
METHODS
Design
Conduct
Analysis
Interpretation
ALTERNATIVE
EXPLANATION
S
Chance
Bias
Confounding
INFERENCES
Epidemiologic
Causal
ACTION
Behavioural
Clinical
Community
Environmental
DESCRIPTIVE
What (case
definition)
Who (person)
Where (place)
When (time)
How many
(measures)
ANALYTIC
Why (Causes)
How (Causes)
28.
Key questionsKey questions
Why now?Why now?
Why here?Why here?
Why in this group?Why in this group?
29.
Descriptive EpidemiologyDescriptive Epidemiology
Study of the occurrence and distribution of
disease
Terms:
Time
Place
Person
30.
What are the three categories ofWhat are the three categories of
descriptive epidemiologic clues?descriptive epidemiologic clues?
□□ Person:Person: WhoWho is getting sick?is getting sick?
□□ Place:Place: WhereWhere is the sickness occurring?is the sickness occurring?
□□ Time:Time: WhenWhen is the sickness occurring?is the sickness occurring?
PPT = person, place, timePPT = person, place, time
32.
Secular TrendSecular Trend
The long-time trend of disease
occurrence
33.
Tetanus – by year, USA, 1955-2000Tetanus – by year, USA, 1955-2000
During 2000, a total of 35 cases of tetanus were reported. The percentage of cases among persons aged 25-59 years
Has increased in the last decade. Note: A tetanus vaccine was first available in 1933.
0
100
200
300
400
500
600
700
800
900
1955 1960 1965 1970 1975 1980 1985 1990 1995 2000
Year
34.
Possible Reasons for Changes inPossible Reasons for Changes in
TrendsTrends
ArtifactualArtifactual
Errors in numerator due toErrors in numerator due to
Changes in the recognition of diseaseChanges in the recognition of disease
Changes in the rules and procedures forChanges in the rules and procedures for
classification of causes of deathclassification of causes of death
Changes in the classification code of causes ofChanges in the classification code of causes of
deathdeath
Changes in accuracy of reporting age at deathChanges in accuracy of reporting age at death
Errors in the denominator due to error in theErrors in the denominator due to error in the
enumeration of the populationenumeration of the population
35.
Possible Reasons for Changes inPossible Reasons for Changes in
Trends (cont.)Trends (cont.)
RealReal
Changes in age distribution of the populationChanges in age distribution of the population
Changes in survivorshipChanges in survivorship
Changes in incidence of disease resultingChanges in incidence of disease resulting
fromfrom
Genetic factorsGenetic factors
Environmental factorsEnvironmental factors
36.
Other phrasesOther phrases
Cyclic trends ~ recurrent alterations in
occurrence , interval or frequency of disease
Secular cyclicity
Levels of immunizations
Build up of susceptibles
e.g. Hep A-7 yr cycle,Measles-2yr cycle
Short term cyclicity
Chickenpox,salmonella(yearly basis)
37.
Periodic TrendPeriodic Trend
Temporal interruption of the general
trend of secular variation
39.
SeasonalSeasonal
A cyclic variation in disease frequencyA cyclic variation in disease frequency
by time of year & seasonby time of year & season..
Seasonal fluctuations in,Seasonal fluctuations in,
Environmental factorsEnvironmental factors
Occupational activitiesOccupational activities
Recreational activitiesRecreational activities
40.
Seasonal TrendSeasonal Trend
Pneumonia-Influenza Deaths – By year,Pneumonia-Influenza Deaths – By year,
1934-19801934-1980
41.
EpidemicEpidemic
An increase in incidence above the expected
in a defined geographic area within a
defined time period
42.
Endemic, Epidemic and Pandemic
Endemic - The habitual presence (or usual occurrence) of a
disease within a given geographic area
Epidemic - The occurrence of an infectious disease clearly in
excess of normal expectancy, and generated
from a common or propagated source
Pandemic - A worldwide epidemic affecting an exceptionally
high proportion of the global population
Number
of Cases
of
Disease
Time
43.
Time clusteringTime clustering
Time Place Cluster/disease clusterTime Place Cluster/disease cluster
A group of cases occur close togetherA group of cases occur close together
& have a well aligned distribution& have a well aligned distribution
patternpattern {{in terms ofin terms of time and placetime and place}}
Cluster analysis-used for rare or special diseaseCluster analysis-used for rare or special disease
events.events.
44.
Time/Place clustering analysis using theTime/Place clustering analysis using the
Poisson modelPoisson model
{Poisson spatial/nearest neighbor distribution}{Poisson spatial/nearest neighbor distribution}
Poisson probability distribution is an inferential statistics probabilityPoisson probability distribution is an inferential statistics probability
measure.measure.
Describes objects/events as they are distributed geographically.Describes objects/events as they are distributed geographically.
Geographical area divided into a series of equal square areas.Geographical area divided into a series of equal square areas.
Randomization i.e. each case has equal probability of falling into eachRandomization i.e. each case has equal probability of falling into each
square.square.
If clustering occurs, probability of cause-effect relationship goes up &If clustering occurs, probability of cause-effect relationship goes up &
vice versa.vice versa.
45.
PlacePlace
Diagnosis is Made
Contact occurred
between agent and
host
Source became
infected
Geographic Area Example Action Level
Home – Patient ill
Restaurant – Food
Eaten
Farm – Eggs Infected
Investigation
Control
Prevention
46.
PersonPerson
Age Hobbies
Sex Pets
Occupation Travel
Immunization status Personal Habits
Underlying disease Stress
Medication Family unit
Nutritional status School
Socioeconomic factors Genetics
Crowding Religion
47.
Descriptive epidemiologyDescriptive epidemiology ::
Patterns of Disease OccurrencePatterns of Disease Occurrence
distributiondistribution of disease in populationsof disease in populations
numerator ( “event” count ) / denominator ( group “atnumerator ( “event” count ) / denominator ( group “at
risk” )risk” )
by “by “personperson” : age , race / ethnicity , gender ,” : age , race / ethnicity , gender ,
occupation , education , marital status , geneticoccupation , education , marital status , genetic
marker , sexual preferencemarker , sexual preference
by “by “placeplace” : residence (urban vs. rural) , worksite ,” : residence (urban vs. rural) , worksite ,
social eventsocial event
by “by “timetime” : week , month , year ; sporadic , seasonal” : week , month , year ; sporadic , seasonal
, trends, trends
--- incubation period ; latency--- incubation period ; latency
48.
Sources of informationSources of information
Census dataCensus data
Vital statistical recordsVital statistical records
Employment health examinationsEmployment health examinations
Clinical records from hospitalsClinical records from hospitals
National figures on food consumption ,National figures on food consumption ,
medications, health events etcmedications, health events etc
49.
Epidemiologic (Epidemiologic ( scientificscientific ) Approach) Approach
1. Identify a PROBLEM1. Identify a PROBLEM ::
clinical suspicion ; case series ; review of medical literatureclinical suspicion ; case series ; review of medical literature
2. Formulate a HYPOTHESIS2. Formulate a HYPOTHESIS ( asking the right question ) ;( asking the right question ) ;
good hypotheses are: Specific, Measurable, and Plausiblegood hypotheses are: Specific, Measurable, and Plausible
3. TEST that HYPOTHESIS3. TEST that HYPOTHESIS ( assumptions vs. type of data )( assumptions vs. type of data )
4. always Question the VALIDITY of the result(s)4. always Question the VALIDITY of the result(s) ::
Chance ; Bias ; and CausalityChance ; Bias ; and Causality
50.
Epidemiologic Study: threats to ValidityEpidemiologic Study: threats to Validity
ChanceChance : role of: role of randomrandom error in outcome measure(s)error in outcome measure(s)
( p - value ; power of the study and the confidence interval )( p - value ; power of the study and the confidence interval )
--- largely determined by sample size--- largely determined by sample size
BiasBias : role of: role of systematicsystematic error in outcome measure(s)error in outcome measure(s)
SelectionSelection bias - subjects not representativebias - subjects not representative
InformationInformation bias - error(s) in subject data / classificationbias - error(s) in subject data / classification
ConfoundingConfounding - 3rd variable (causal) assoc. w/ both X and Y- 3rd variable (causal) assoc. w/ both X and Y
51.
What is a hypothesis?What is a hypothesis?
An educated guessAn educated guess
an unproven ideaan unproven idea
based on observation or reasoning, that can bebased on observation or reasoning, that can be
proven or disproven through investigation.proven or disproven through investigation.
52.
What goes into a hypothesis?What goes into a hypothesis?
Characteristics of the diseaseCharacteristics of the disease
The illnessThe illness
Established modes of transmissionEstablished modes of transmission
DistributionDistribution
In timeIn time
By placeBy place
By personBy person
53.
Hypothesis formulationHypothesis formulation
4 methods {derived from4 methods {derived from 5 canons of inductive5 canons of inductive
reasoningreasoning by John Stuart Mill}by John Stuart Mill}
Method of differenceMethod of difference
Method of agreementMethod of agreement
Method of concomitant variationMethod of concomitant variation
Method of analogyMethod of analogy
54.
MeasuresMeasures
Morbidity: Refers to the presence of disease in aMorbidity: Refers to the presence of disease in a
populationpopulation
Mortality: Refers to the occurrence of death in aMortality: Refers to the occurrence of death in a
populationpopulation
55.
Methods for MeasuringMethods for Measuring
How do we determine disease frequency for aHow do we determine disease frequency for a
population?population?
Rate = Frequency of defined events in specifiedRate = Frequency of defined events in specified
population for given time periodpopulation for given time period
Rates allow comparisons between two or moreRates allow comparisons between two or more
populations of different sizes or of a populationpopulations of different sizes or of a population
over timeover time
56.
Compute Disease RateCompute Disease Rate
Number of persons at risk = 5,595,211Number of persons at risk = 5,595,211
Number of persons with disease = 17,382Number of persons with disease = 17,382
Rate =Rate = 17,382 persons with heart disease17,382 persons with heart disease
5,595,211 persons5,595,211 persons
== ..003107 heart disease / resident / year003107 heart disease / resident / year
57.
RatesRates
Rates are usually expressed as integers andRates are usually expressed as integers and
decimals for populations at risk during specifieddecimals for populations at risk during specified
periods to make comparisons easier.periods to make comparisons easier.
.003107 heart disease / resident / year.003107 heart disease / resident / year x 100,000x 100,000
== 310.7310.7 heart disease /heart disease / 100,000100,000 residents / yearresidents / year
58.
PrevalencePrevalence vsvs. Incidence. Incidence
Prevalence is the number ofPrevalence is the number of existingexisting cases ofcases of
disease in the population during a defineddisease in the population during a defined
period.period.
Incidence is the number ofIncidence is the number of newnew cases ofcases of
disease that develop in the population during adisease that develop in the population during a
defined period.defined period.
59.
IncidenceIncidence
Incidence rate is a measure of theIncidence rate is a measure of the
probability of the event among persons atprobability of the event among persons at
risk.risk.
60.
Incidence RatesIncidence Rates
Population denominator:Population denominator:
IR =IR = # new cases during time period X K# new cases during time period X K
specified populationspecified population at riskat risk
61.
Example (Incidence Rate)Example (Incidence Rate)
During a six-month time period, a total of 53 nosocomialDuring a six-month time period, a total of 53 nosocomial
infections were recorded by an infection control nurseinfections were recorded by an infection control nurse
at a community hospital. During this time, there wereat a community hospital. During this time, there were
832 patients with a total of 1,290 patient days. What is832 patients with a total of 1,290 patient days. What is
the rate of nosocomial infections per 100 patient days?the rate of nosocomial infections per 100 patient days?
I R =
53 X 100
1,290 pt. days
=
4.1 infections per
100 pt. days
62.
Mortality RatesMortality Rates
A special type of incidence rateA special type of incidence rate
Number of deaths occurring in a specifiedNumber of deaths occurring in a specified
population in a given time periodpopulation in a given time period
63.
Use of Mortality ratesUse of Mortality rates
Mortality rates are used to estimate diseaseMortality rates are used to estimate disease
frequency when…frequency when…
incidence data are not available,
case-fatality rates are high,
goal is to reduce mortality among screened or
targeted populations
64.
Mortality Rates: ExamplesMortality Rates: Examples
Crude mortalityCrude mortality: death rate in an entire: death rate in an entire
populationpopulation
Rates can also be calculated for sub-groups withinRates can also be calculated for sub-groups within
the populationthe population
Cause-specific mortalityCause-specific mortality: rate at which deaths: rate at which deaths
occur for a specific causeoccur for a specific cause
65.
Mortality Rates: ExamplesMortality Rates: Examples
Case-fatalityCase-fatality: Rate at which deaths occur from a: Rate at which deaths occur from a
disease among those with the diseasedisease among those with the disease
Maternal mortalityMaternal mortality: Ratio of death from: Ratio of death from
childbearing for a given time period per numberchildbearing for a given time period per number
of live births during same time periodof live births during same time period
66.
Mortality Rates: ExamplesMortality Rates: Examples
Infant mortalityInfant mortality: Rate of death for children less: Rate of death for children less
than 1 year per number of live birthsthan 1 year per number of live births
Neonatal mortalityNeonatal mortality: Rate of death for children: Rate of death for children
less than 28 days of age per number of liveless than 28 days of age per number of live
birthsbirths
67.
PrevalencePrevalence
Prevalence: Existing cases in a specifiedPrevalence: Existing cases in a specified
population during a specified time period (bothpopulation during a specified time period (both
new and ongoing cases)new and ongoing cases)
Prevalence is a measure of burden of disease orPrevalence is a measure of burden of disease or
health problem in a populationhealth problem in a population
68.
PrevalencePrevalence
Prevalence: The number of existing cases in thePrevalence: The number of existing cases in the
population during a given time period.population during a given time period.
PRPR == # existing cases during time period# existing cases during time period
population at same point in timepopulation at same point in time
Prevalence rates are often expressed as a percentage.Prevalence rates are often expressed as a percentage.
69.
Factors Influencing PrevalenceFactors 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
70.
Basic Measures of AssociationBasic Measures of Association
Relative risk& odds ratioRelative risk& odds ratio
We often need to know the relationship betweenWe often need to know the relationship between
an outcome and certain factors (e.g., age, sex,an outcome and certain factors (e.g., age, sex,
race, smoking status, etc.)race, smoking status, etc.)
Used to guide planning and interventionUsed to guide planning and intervention
strategiesstrategies
71.
2 x 2 contingency table for Calculation of2 x 2 contingency table for Calculation of
Measures of AssociationMeasures of Association
Outcome Outcome
ExposureExposure PresentPresent AbsentAbsent TOTALTOTAL
PresentPresent aa bb a+ba+b
AbsentAbsent cc dd c+dc+d
TOTALTOTAL a+ca+c b+db+d a+b+c+da+b+c+d
Note: “Exposure” is a broad term that represents any
factor that may be related to an outcome.
72.
Relative RiskRelative Risk
Ratio of the incidence rates between two groupsRatio of the incidence rates between two groups
Can only be calculated from prospective studiesCan only be calculated from prospective studies
(cohort studies)(cohort studies)
InterpretationInterpretation
RR > 1: Increased risk of outcome among “exposed”RR > 1: Increased risk of outcome among “exposed”
groupgroup
RR < 1: Decreased risk, or protective effects, amongRR < 1: Decreased risk, or protective effects, among
“exposed” group“exposed” group
RR = 1: No association between exposure andRR = 1: No association between exposure and
outcomeoutcome
73.
Calculation of Relative RiskCalculation of Relative Risk
incidence rate among exposedincidence rate among exposed
RR =RR =
incidence rate among non-exposedincidence rate among non-exposed
74.
Calculation of Relative RiskCalculation of Relative Risk
OutcomeOutcome
ExposureExposure PresentPresent AbsentAbsent TOTALTOTAL
PresentPresent aa bb a+ba+b
AbsentAbsent cc dd c+dc+d
TOTALTOTAL a+ca+c b+db+d a+b+c+da+b+c+d
Relative Risk =
a
a b
c
c d
+
+
75.
Relative Risk Case StudyRelative Risk Case Study
Birth WeightBirth Weight
Smoking statusSmoking status <2500 g<2500 g >>2500 g2500 g TOTALTOTAL
SmokerSmoker 120120 240240 360360
Non-smokerNon-smoker 6060 580580 640640
TOTALTOTAL 180180 820820 10001000
Smoking and low birth weight
76.
Answers to Relative Risk Case StudyAnswers to Relative Risk Case Study
1. Incidence of LBW among1. Incidence of LBW among
smokerssmokers
2. Incidence of LBW among2. Incidence of LBW among
non-smokersnon-smokers
3.3. Relative riskRelative risk for having afor having a
LBW baby among smokersLBW baby among smokers
versus non-smokersversus non-smokers
= =
1 2 0
3 6 0
1 0 0 0 3 3 3 3x , .
= =
6 0
6 4 0
1 0 0 0 9 3 8x , .
= ≈
3 3 3 3
9 3 8
3 6
.
.
.
77.
Understanding Probability and OddsUnderstanding Probability and Odds
Probability:Probability: Chance or risk of an event occurring (aChance or risk of an event occurring (a
proportion)proportion)
Probability=Probability= no. of times an event occursno. of times an event occurs
no. of times an event can occurno. of times an event can occur
Odds:Odds: ratio of the probability of an event occurring toratio of the probability of an event occurring to
the probability of an event not occurringthe probability of an event not occurring
Odds = P/(1-P)Odds = P/(1-P)
78.
Calculation of Odds RatioCalculation of Odds Ratio
OutcomeOutcome
ExposureExposure PresentPresent AbsentAbsent TOTALTOTAL
PresentPresent aa bb a+ba+b
AbsentAbsent cc dd c+dc+d
TOTALTOTAL a+ca+c b+db+d a+b+c+da+b+c+d
Odds Ratio =
a d
b c
79.
Odds RatioOdds Ratio
The odds ratio (OR) is a ratio of two odds.The odds ratio (OR) is a ratio of two odds.
The OR can be calculated for all three studyThe OR can be calculated for all three study
designsdesigns
Cross-sectionalCross-sectional
Case-controlCase-control
Cohort.Cohort.
80.
Various approaches to Odds ratioVarious approaches to Odds ratio
Cross product/odds ratioCross product/odds ratio
2 x 2 contingency table (ad/bc)2 x 2 contingency table (ad/bc)
Prevalence odds ratioPrevalence odds ratio
cross sectional studiescross sectional studies
Exposure odds ratioExposure odds ratio(( odds of exposure in diseased vs. nondiseased)odds of exposure in diseased vs. nondiseased)
In rare cases or exotic diseasesIn rare cases or exotic diseases
Disease odds/Rate odds ratioDisease odds/Rate odds ratio(o(odds of getting a disease if exposeddds of getting a disease if exposed
or unexposed)or unexposed)
Cohort & cross sectionalCohort & cross sectional
Risk odds ratioRisk odds ratio
Cross sectional ,cohort & case controlCross sectional ,cohort & case control
81.
Odds RatioOdds Ratio
For cohort & cross sectional studiesFor cohort & cross sectional studies: OR is a: OR is a
ratio of the odds of the outcome in exposedratio of the odds of the outcome in exposed
persons to the odds of the outcome in non-persons to the odds of the outcome in non-
exposed persons.exposed persons.
For case-control studiesFor case-control studies: OR is a ratio of the: OR is a ratio of the
odds of exposure in cases to the odds ofodds of exposure in cases to the odds of
exposure in controls.exposure in controls.
Provides an estimate of the relative risk whenProvides an estimate of the relative risk when
the outcome is rarethe outcome is rare
82.
Interpretation of Odds RatioInterpretation of Odds Ratio
OR > 1: Increased odds of exposure among thoseOR > 1: Increased odds of exposure among those
with outcomewith outcome
OR < 1: Decreased odds, or protective effects,OR < 1: Decreased odds, or protective effects,
among those with outcomeamong those with outcome
OR = 1: No association between exposure andOR = 1: No association between exposure and
outcomeoutcome
83.
Keeping the Terms StraightKeeping the Terms Straight
““Risk ratio” = “relative risk”Risk ratio” = “relative risk”
““Relative odds” = “odds ratio”Relative odds” = “odds ratio”
Remember – the key is recognizing the termsRemember – the key is recognizing the terms
“risk” and “odds”“risk” and “odds”
84.
Appropriateness of MeasuresAppropriateness of Measures
Remember that the relative risk can only beRemember that the relative risk can only be
calculated in prospective studiescalculated in prospective studies
Odds ratio can be calculated for any designOdds ratio can be calculated for any design
Cohort / prospectiveCohort / prospective
Case-controlCase-control
Cross-sectionalCross-sectional
85.
InferenceInference
The relative risk and odds ratio provide theThe relative risk and odds ratio provide the
magnitude of difference between some factormagnitude of difference between some factor
and an outcomeand an outcome
How do we know if the magnitude isHow do we know if the magnitude is statisticallystatistically
significant?significant?
86.
Confidence IntervalsConfidence Intervals
A confidence interval is a range of values that isA confidence interval is a range of values that is
likely (e.g., 95%) to contain the true value in thelikely (e.g., 95%) to contain the true value in the
underlying populationunderlying population
87.
The 10 Steps of Outbreak InvestigationThe 10 Steps of Outbreak Investigation
Prepare for field workPrepare for field work
Establish the existence of an outbreakEstablish the existence of an outbreak
Verify the diagnosisVerify the diagnosis
Define & identify casesDefine & identify cases
PerformPerform descriptive epidemiologydescriptive epidemiology
Develop hypothesesDevelop hypotheses
PerformPerform analytic epidemiologyanalytic epidemiology
Refine hypotheses & conduct additional studiesRefine hypotheses & conduct additional studies
Implement control & prevention measuresImplement control & prevention measures
Communicate findingsCommunicate findings
88.
Objectives of Descriptive EpidemiologyObjectives of Descriptive Epidemiology
To evaluate trends in health and disease and allowTo evaluate trends in health and disease and allow
comparisons among countries and subgroups withincomparisons among countries and subgroups within
countriescountries
To provide a basis for planning, provision andTo provide a basis for planning, provision and
evaluation of servicesevaluation of services
To identify problems to be studied by analytic methodsTo identify problems to be studied by analytic methods
and to test hypotheses related to those problemsand to test hypotheses related to those problems