principles of epidemiology epidemiology • epidemiology is an old lineage born with man. adem, eve,...
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Principles of Epidemiology
Dr Mustafa Sagri
Zawia medical college
Community medicine department
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Epidemiology
• Epidemiology is an old lineage born with man.
Adem, Eve, and the Apple
• Slow progress over time.
• Rapid progress during the last four decades.
• Infectious & chronic diseases.
• Now it is branch of many subjects & specialties.
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Epidemiology
• Infectious diseases epidemiology
• Chronic diseases epidemiology
• Clinical epidemiology
• Malaria epidemiology
• Cancer Epidemiology
• ect ….
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Introduction4
The epidemiologic perspective
•Epidemiology is a way of thinking
about health – human ecology
•Much more than a collection of
methods – a way of using them
•Epidemiologists consider context,
heterogeneity, dynamics, inference
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Introduction5
What is epidemiology, really?
•Study of the health and disease of the
“body politic” – the population.
•Basic science of public health
•What causes disease?
•How does disease spread?
•What prevents disease?
•What works in controlling disease?
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Introduction6
What for?
1. Provide the scientific basis to prevent
disease & injury and promote health.
2. Determine relative importance to
establish priorities for research & action.
3. Identify sections of the population at
greatest risk to target interventions.
4. Evaluate effectiveness of programs in
improving the health of the population.
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Introduction7
What for? – more
5. Study natural history of disease from
precursor states through clinical course
6. Conduct surveillance of disease and
injury occurrence in populations
7. Investigate disease outbreaks
– Milton Terris, The Society for Epidemiologic Research (SER) and the
future of epidemiology. Am J Epidemiol 1992; 136(8):909-915, p 912
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Introduction8
Natural history of disease
• Disease is a process
• Natural history is the entire process of development of a disease
• Tells us what we can expect to happen
• Fundamental concept for studying and controlling disease
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Introduction9
Course objectives1. Explain the population perspective, access
population data, describe public health
problems
2. Apply and interpret measures of disease
occurrence and correlates in populations
3. Use basic methods for investigating disease
outbreaks
4. Explain relative strengths and limitations of
different epidemiologic study designs
5. Identify and control major sources of error in
community health studies
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Introduction10
Course objectives – continued
6. Evaluate epidemiologic evidence by applying criteria for causal inference
7. Use epidemiologic methods in evaluating
public health interventions
8. Comprehend basic ethical and legal
principles related to epidemiologic data
9. Appreciate complexities in applying
scientific evidence in making policy
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Definition of Epidemiology:
The study of the distribution anddeterminants of disease and healthrelated states or events in aspecified population, and theapplication of this study to thecontrol of health problems
• epi = upon , demos = people , and logus = science
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Anatomy of the definition
1) Study.
2) Distribution.
3) Determinants.
4) health related states.
5) Population.
6) Control.
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Anatomy of the definition
1)Study.
It based principles of Statistics & research methodology
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Anatomy of the definition
2) Distribution.
by Disease. Triad (time, person & place)
When, where and who ???? (descriptive studies)
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Anatomy of the definition
3) Determinants.
Causes or risk factors, how?? and why??
(analytic studies)
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Anatomy of the definition
4) Health related states.
The whole spectrum of health status.
Infectious diseases
ND’s
Risks factors: smoking, life-style, obesity ect ..
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Anatomy of the definition
5) Population.
The whole or groups rather than individuals.
Base for calculation (denominatio)
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Anatomy of the definition
6) Control.
Developing & evaluating interventions to control.
Control stages
➢ Control
➢ Elimination
➢ Eradication
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Epidemiological approach
Epidemiological approach to problems
of health & diseases is based on: -
1) Asking questions:
Related to health events: what is the event, its size
Related to health action: how can it be prevented
2) Getting answers: to have clues & explanation
3) Making comparison
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The Scope of Epidemiology
in detail
1) To study historically the rise & fall of
disease in population:
e.g. epidemics, fluctuation, changes and trends
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The Scope of Epidemiology
in detail
2) Community diagnosis:
Health problems in terms of morbidity and
mortality.
Understanding of social & behavioural patterns
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The Scope of Epidemiology
in detail
3) Planning and evaluation
of the health programs that implement
preventive and control measures for specific
diseases. Planning is essential for proper
allocation of the limited resources.
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The Scope of Epidemiology
in detail
4) Evaluation of individual’s risks & chances.
Besides incidences and prevalences one can calculates odds ratios, risk factors, and attributable risks
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The Scope of Epidemiology
in detail
5) Syndrome identification
by observing frequently associated findings in
individual patients, e.g., CRS & AIDS.
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The Scope of Epidemiology
in detail
6) Describing the natural history of a disease.
Prepathogenesis & pathogenesis
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The Scope of Epidemiology
in detail
7) Searching & Identifying causes & risks
factors that can be modified to prevent the
occurrence or spread of the disease.
Epidemiological studies have been used to test
the effectiveness of vaccination, mass
treatment, and health education as measures to
prevent spread of the disease among
population.
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Epidemiological Methods
Epidemiologic Study
Designs
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Epidemiologic Study Designs
Grimes & Schulz, 2002 (www)
Longitu
dinal
study
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Classifications
1 – observational studies allow nature to take its own
course. Here investigator measures but does not intervene.
A Descriptions of occurrence of disease in the populations.
Simple descriptive studies
- Cross – sectional or prevalence study – with Individuals as
unit of study
- Longitudinal study ( gets Incidence) – with Individuals as
unit of study
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Descriptive Epidemiology
• First phase of an epidemiological
investigation.
• When?? ------ Time distribution
• Where?? ------ Place distribution
• Who?? ------ Person distribution
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Procedures of Descriptive
studies
• Defining the Population
• Defining the disease
• Describing the disease
– Time / Place / Person
• Measurement of disease
• Comparison with known indices
• Formulation of an aetiological hypothesis
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I. Defining the Population
• In terms of total number
• In terms of
– Age
– Sex
– Occupation
– Cultural characters
It provides denominator for calculating rates
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II. Defining the disease under study
• Purpose: to identify those who have & do
not have disease.
• Operational definition: Definition by which
the disease or condition can be identified
& measured with a degree of accuracy.
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How do you describe a
disease?Measles Symptoms and Signs
– Symptoms - High grade fever, Redness of
eyes and Rash
– Signs - Rash, Koplick’s spots
– We can describe the disease in a community
in a scientific way – Descriptive epidemiology
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III. Describing the disease
• Time
– Year / season / month / week/ day / hour of onset
• Place
– Climate zone / country / region /urban /rural / local community / town / city
• Person
– Age / sex / Marital status / Occupation / social status / Education
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Three kinds of time trends or fluctuations:
I Short – term fluctuations
II Periodic fluctuations
III Long term - fluctuations
Time Distribution
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Time distribution - Uses
• Take appropriate action
• Know whether interventions are effective
• Develop hypothesis regarding the source
or cause of outbreak
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Place distribution
• Describes the distribution of cases in a geographic
area
• The distribution can be based on place of
residence, place of work, place of recreation, place
of travel etc depending on the disease
• We may have to try more than one distribution to
learn more about the disease
• Two types of maps - Spot map and Area map
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Place distribution - uses
• Know the geographical extent of disease
• Identify the source of infection or causative
agent
• To plan control or preventive measures
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Person distribution
• Personal characteristics like age, sex etc.
almost invariably affect disease occurrence
• So distribution of disease or health event
among these categories help the
epidemiologist in knowing more about the
disease
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Person distribution - age
• Almost every health related event vary
with age
– Measles
– Cancer
– Hypertension
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Person distribution (sex)
• Distribution of disease varies between
males and females
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Person distribution – other attributes
• Race
• Ethnicity
• Nationality
• Behaviour
• Socioeconomic groups
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IV. Measurement of Disease :-
• It must be known the amount of disease in the populations
ie by mortality, morbidity disability – etc.
• Incidence obtained from longitudinal studies (repeated
observations in same population).
• Prevalence obtained from cross – sectional studies (single
observation in a population).
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V. Comparing with known indices
⚫ It is essential to compare between populations & sub-groups of
populations.
⚫ It gives clues to disease aetiology. We can also identify or define
who are at increased risk for certain disease.
VI. Formulations of hypothesis
⚫ A hypothesis is a supposition arrived at from observations or
reflections.
⚫ It can be accepted or rejected using the techniques of analytical
epidemiology.
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Cross sectional studies :-
• It is also called prevalence study. It is based on a
single examination of cross section of population at
one point in time.
• The result can be projected on the whole population.
• Photograph & video.
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Aims of cross – sectional studies
⚫ To find the disease pattern in the community and to
measure the disease burden
⚫ To find the prevalence rates of various disease
⚫ To formulate aetiological hypothesis
⚫ To find the risk groups of various disease
⚫ To find out risk factors
⚫ Useful for screening of populations groups for
undiagnosed disease of public health importance.
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Advantage :-
1) Requires short durations, less costly .
2) It is more advantage than case control study .
3) Useful for screening of diseases.
4) Provides useful data for health care deliverysystems.
Disadvantages :-
1) They will not provide direct estimates of risk.
2) They are prone to bias from selective interval.
3) Exposure and disease are measured at the samepoint of time so little information's about theoccurrence of new cases.
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Longitudinal Studies :- Longitudinal studies are
repeated in the same population over a prolonged
period of time by means of follow –up examinations.
This study will provide-
a) Incidence.
b) Natural history of disease.
c) Association of risk factors and the development of
disease.
d) The essential difference between this & cohort
studies is there is no control groups.
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Advantages :-
1) Suitable for common diseases of high incidence.
2) Gives fairly reliable results.
3) Useful to fill up the gaps in the natural history of
disease.
Disadvantages :-
1) Needs bigger size of sample.
2) Attrition, (dropouts during study period).
3) Needs prolonged period of follow up.
4) Higher operational costs.
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Uses of descriptive Epidemiology :-
1) It provides disease burden ie mortality & morbidity
2) Provides clues to aetiology and help formulation
of hypothesis
3) Provides data for planning, organizing and
evaluating preventive & curative services
4) Contribute to research ie disease occurrence by
time, place and person.
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Analytical Epidemiology
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Epidemiologic Study Designs
Grimes & Schulz, 2002 (www)
Longitu
dinal
study
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Analytical epidemiology
• Analytic studies are the second major type of
epidemiological studies
• An important feature of analytical epidemiology
is the presence of a comparison group
• The objective of Analytical epidemiology is to
test Hypotheses 54
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Analytical epidemiology
• Finds out the determinants of the disease
• When we know the determinants of the
disease we can control the disease and
prevent the disease
• Makes the community healthy
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Analytical epidemiology
• There are two types of studies
– Case-Control study
– Cohort study
From these we can determine: -
• Whether or not a statistical association
exists between a disease and a suspected
factor;
• If the association exists, what is the
strength of it?
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Case-Control study
• The case-control study is a basically
comparison study.
• It is considered nowadays one of the most
important methods in dealing with causal
hypothesis testing.
• It involves two groups of the cases and the
controls which are similar in all respects
except for disease.
• Compares the exposure among cases (i.e.,
individuals with disease) and controls (i.e.,
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Case-Control study
It has three characteristics
• both exposure and out come occurred
before the study
• it proceeds backwards from effect to cause
• uses a control(comparison group)to
support or refute
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Design of a Case Control studyTHE BASIC DESIGN OF CASE CONTROL STUDY IS:-
The framework of a case-control study (THE 2 X 2
CONTINGENCY TABLE)
Cases
(Disease+)
Control
(Disease-)
Risk factor
present(+)a b
Risk factor
absent (-)c d
a+c b+d
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Design of Case Control study
a b
c d
a+c b+d
Cases
(Disease +)
Control
(Disease -)
Risk factor +
Risk factor -
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Steps in a Case Control study
• Selection cases and controls
• Matching
• Measurement of exposure to risk factor
• Analysis and interpretation
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Selection of Cases
• Cases selected should have the correct
diagnosis
• Only cases with the confirmed diagnosis
should be included
• Controls must be FREE from the disease
under study.
• If there are sub-clinical cases, do
laboratory test to make sure that the
person has no disease
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Sources of controls
• Hospitals (patients having other disease)
• Neighborhood controls
• General population
• How many controls will you take for a case?
– In large studies generally 1
– In small studies (below 50) up to 4
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Matching
• Matching is a process by which we select
controls in a such a way that they are
similar to cases in important variables
• Age, Sex, Occupation etc.
• By matching we can neutralize any
confounding factor
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Matching - examples
• For studying Lung cancer the Controls should be
males and not females
• For studying Lung cancer the Controls should be
adult males and not small boys
• For studying Breast cancer the controls should
be females and not males!
• For studying Breast cancer the controls should
be adult females and not small girls
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Measurement of exposure to cause
• There must be a clear Definition for the
risk factor.
• That should be same for Cases and
Controls
• E.g. Smoking- no. of cigarettes, duration
of smoking, type of cigarette etc.
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Analysis
• Calculate exposure rates among cases
and controls
• Calculate the disease risk associated with
exposure (Odds ratio)
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Cigarette smoking and Lung cancer
• Descriptive epidemiology of Lung cancer
patients was done and the following are
the important characteristics
– Males
– Cigarette smokers
• Hypothesis is ‘cigarette smoking is the
cause for lung cancer’
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Analysis
Exposure rate to smoking
Cases = a/a+c 33/35 = 94.2%
Controls = b/b+d 55/82 = 67%
Cases (Lung
cancer +)Controls ( No
lung cancer)
Smoking +
Smoking -
33(a) 55(b)
2(c) 27(d)
35(a+c) 82(b+d)
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Estimation of risk
• Those who are having lung cancer are
smoking more(94.2%)
• However it does not mean that 94.2% of
all smokers will develop lung cancer.
• We estimate risk to develop lung cancer in
smokers by calculating ‘Odds ratio’
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Odds ratio
Odds ratio = ad/bc
33x27/55x2 = 8.1
Those who smoke have 8.1 times the risk of developing Lung cancer than those who do not smoke
If the odds ratio is 1 means no risk
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P- value
• We have found cigarette smokers has 8.1 times more risk of getting Lung cancer
• There are thousands of Lung cancer patients in the world
• We have taken only a small sample of 35 cases
• How do we know it is true for all lung cancer patients?
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P-value
• To see if this association is due to chance
• It is the probability that the difference is
due to chance
• If P value is <0.05 it is considered
significant
– P value in lung cancer study is <0.001
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Analysis
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CC study - advantages
• Easy to conduct
• Inexpensive
• No risk to people
• No attrition (loss of patients) problems
• No ethical problems
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CC study - disadvantages
• Problem of accuracy of data
– Loss of memory
• How many cigarettes a person smoked 20 years
ago?
– Incomplete records
• What medicine a lady took in pregnancy?
• Getting good controls is difficult
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Advantages Disadvantages
1) Easy to carry out.
2) Rapid and inexpensive.
3) Requires few subjects.
4) Suitable for rare disease.
5) No risk to subjects.
6) Can study several risk factors
7) Factors can be identified &
prevention can be established.
8) No attrition.
9) Ethical issue is minimal.
1) Problem of bias. ACCURACY
UNCERTAIN
2) Selection OF APPROPRIATE
CONTROL IS is difficult.
3) Relative risk is only estimated NO
INCIDENCECALCULATED.
4) Not suitable to the evaluation of therapy
or prophylaxis.
5) Representativeness of cases and controls
is a major concern.
6) No distinguish between causes &
associated factors (smoking & air
pollution)
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Cohort study
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Contents• Definition of cohort
• Design of study
• Selection of Study Cohort and Control Cohort
• Calculation of Incidence rates
• Calculation of Relative risk
• Calculation of ‘P’ value
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Cohort• Is a group of persons who are exposed to
the suspected aetiological agent are
compared with matched control subjects
who have not been similarly exposed
• Is a group of people who share a common
characteristic or experience
– People born on a same day
– Students who joined college in a year
– Students from Ajilat, students from Zawia
– People doing same work e.g. doctors
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Cohort study• Also called Prospective study “forward-
looking” or Incidence study
• Is usually done after doing Case-Control
study to get more proof of the cause of
disease
• The study is done on people before the
disease occurs; the starting point is a
group of people exposed to suspected
cause
• The diagnostic criteria of the disease must
be defined beforehand
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INDICATION FOR COHORT
STUDIES:-
• 1)When there is a good evidence of
association between exposure to risk
factors and disease; derived from
descriptive studies and clinical
observations.
• 2) When exposure is rare but with high
incidence among the exposed
• 3)When the attrition(drop out) is low which
can be minimized by follow up, stability of
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Design of Cohort study
a b a+b
c d c+d
a+c b+d
Study Cohort
Risk factor +
Control Cohort
Risk factor +
Disease + Disease -
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Elements of a Cohort study1. Selection of study subjects
2. Selection of comparison (control) group
3. Data collection and Follow-up
4. Analysis
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Selection of Study Cohort
• They are selected from general population
or from specific groups e.g. Doctors,
students etc.
• Members of the study cohort must be
FREE of disease
• Members of the study cohort must be
exposed to the risk factor
• The members should be susceptible to the
disease
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Selection of Control Cohort• They are selected from general population or
from specific groups e.g. Doctors, students etc.
• Members of the control cohort must be FREE
of disease
• Members of the control cohort must NOT be
exposed to the risk factor
• The members should be equally susceptible to
the disease
• Members of the control cohort must be similar
[matched] to the study cohort in respect of all
possible variables: age, sex etc.
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Follow up• Both the Study cohort and Control cohort is
followed up to see how many develop the disease
• This is done by
– Medical examination
– Personal visit, Phone call etc.
• Follow up is difficult because some persons will not respond
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Analysis of Cohort study• Incidence rate of disease among Study
cohort is calculated
• Incidence rate of disease among Control
cohort is calculated
• Then Relative Risk is calculated
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Smoking and Lung cancer
7000
a+b
3000
c+d
a+c b+d
Study Cohort
Smoking +
Control Cohort
Smoking -
Disease +
Lung cancer +
Disease –
No Lung cancer
70
(a)
6930
(b)
3
(c)
2997
(d)
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7000
a+b
3000
c+d
a+c b+d
Study Cohort
Smoking +
Control Cohort
Smoking -
Disease +
Lung cancer +
Disease –No Lung cancer
70
(a)
6930
(b)
3
(c)
2997
(d)
Incidence rate among smokers = 70/7000 = 10 per 1000
Incidence rate among non-smokers = 3/3000 = 1 per 1000
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Relative risk
= Incidence of disease among exposed
Incidence of disease among non-exposed
10/1= 10
If relative risk is 1 that means there is no risk
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Advantage of Cohort study• Incidence can be calculated
• More than one disease due to the risk
factor can be studied
– Smoking and Lung cancer, peptic ulcer,
Coronary heart disease etc.
• Gives better proof of the risk factor than
Case Control study
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Disadvantages• It takes long time to complete study
• Persons may lose interest and will not come for follow-up
• The person who is doing the study may lose interest or take another job
• Cohort studies are expensive
• More ethical problems
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95
Summary
• Epidemiologist has to describe data on
diseases on three important
characteristics - Time, Place and Person
• Describing the distribution of disease in
Time, Place and Person helps in
understanding the problem in all
dimensions
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96
Summary
• Study of these distributions will give the
epidemiologist clues regarding the cause
of disease – Hypothesis
• It is also important for
– Implementing health interventions
– Evaluation of health services
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Summary
• Case Control study is used to test
hypothesis
• It involves four steps
– Selection of cases and controls
– Matching
– Measuring exposure
– Analysis (Exposure rate, Odds ratio and P
value)
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Summary
• The analysis of
Case Control study
is by a
2x2 design
• Exposure rates are
calculated among
cases and controls
Dis + Dis -
RF + a b
RF - c d
a+c b+d
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Summary
• Odds ratio is calculated to estimate the
risk of disease among those who are
exposed to the cause
• P value is calculated to know whether the
difference is statistically significant
• Case Control study helps us prove the
cause of disease
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Summary• Cohort study gives better proof of the
cause of disease
• A group of people (study cohort) with the
risk factor is selected
• Another group of people (control cohort)
without the risk factor is selected
• Both groups are followed up to see how
many develop disease
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Summary• Incidence rate of disease is calculated
among study cohort
• Incidence rate of disease is calculated
among the control cohort
• Relative risk is calculated
• Cohort study is more difficult and
expensive than Case Control study
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102
What purpose does it serve?
1. Epidemiologist becomes familiar with the data
and thereby the problem
2. Epidemiologist learns the extent/size of the
problem
3. Epidemiologist creates a detailed description
which can be communicated
4. Identify high risk group(s) and get a clue into the
causation of disease (Hypothesis)
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THANK YOU
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../8/2018Intervention studies104
Study designs: Intervention trials
Principles of Epidemiology for Public Health (EPID600)
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Topics for this lecture
• Experimental and observational
epidemiologic study designs
• Types of intervention trials
• Methodological issues
• Ethical issues
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Experimental and observational
studies• Analytic epidemiologic studies compare
“exposed” to “unexposed” groups, but
epidemiologists usually observe exposures
rather than assign them.
• In experimental (intervention) studies, the
researcher determines who is exposed.
• Most epidemiologic studies are
observational – but intervention studies
have a special status
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Intervention studies107
Analytic study designs
• Intervention trials (experimental)
• Cohort studies (observational)
• Case-control studies
(observational)
• Cross-sectional studies
(observational)
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Types of intervention studies
Therapeutic trials vs. preventive trials
Example of a therapeutic trial:
The β-Blocker
Heart Attack
Trial (B-HAT)
The β-Blocker Heart Attack trial.
JAMA, Nov. 6, 1981;246(18):2073
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Types of intervention studies
Example of a prevention trial:
Perinatal
transmission
of HIV
(ACTG 076)
NEJM 11/3/1994;
331(18):1173-1180
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Randomized trial experience
Photography for Quit for Life: Pinderhughes Photography (New York, NY),
Design: Advertising and Communications, Inc. (Durham, NC)
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randomized trial experience
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Types of intervention studies
The distinction between therapeutic
and preventive is not always a
clear one
Examples:
Community trials of STI treatment
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Types of intervention studies
Clinical trials – intervention is applied to
individuals (patients, students, workers)
• Multiple Risk Factor Intervention Trial
(MRFIT)
Community trials – intervention is applied to
groups (schools, worksites, communities)
• Smoking prevention & cessation (COMMIT)
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Types of intervention studies
• Intervention randomly assigned
• Intervention not randomly
assigned
Randomization is a key feature
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Randomization
Why is randomized assignment of
intervention so important?
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Why is randomized
assignment of intervention so
important?
Randomization is so important
because overall, it provides the
strongest evidence for causal
inference
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Why is randomized
assignment of intervention so
important?1. Best assurance that control group
(unexposed) is a valid substitute
population (avoids self-selection of
exposure)
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Why is randomized
assignment of intervention so
important? 1. Best assurance that control group
(unexposed) is a valid substitute
population
2. Only way to control for unknown
factors
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Why is randomized
assignment of intervention so
important?1. Best assurance that control group
(unexposed) is a valid substitute
population
2. Only way to control for unknown
factors
3. Facilitates masking of exposure status
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Intervention studies120
1. Best assurance that control group (unexposed) is a valid substitute population
2. Only way to control for unknown factors
3. Facilitates masking of exposure status
4. Avoids ambiguity of time order of
exposure and outcome (most intervention
studies achieve this)
Why is randomized
assignment of intervention so
important?
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Intervention studies121
Why is randomized
assignment of intervention so
important?1. Best assurance that control group (unexposed)
is a valid substitute population
2. Only way to control for unknown factors
3. Facilitates masking of exposure status
4. Avoids ambiguity of time order of exposure
and outcome (most intervention studies
achieve this)
5. Provides foundation for statistical tests –valid quantification of uncertainty
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Ethical issues
• Equipoise – there must be genuine
uncertainty about which treatment
is better
• Is it ethical to test something other
than the best?
• After the trial, who will receive the
benefits? The control group?
Everyone?
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Intervention studies123
The Water Pistol
When a 3-year-old boy opened his birthday gift from his grandmother, he discovered a water pistol. He squealed with delight and
headed for the nearest sink.
The boy's father was not so pleased. He turned to his mother and said, “I'm surprised
at you. Don't you remember how I used to drive you crazy with water guns?”
Mom smiled and then replied … “I remember.”
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Thank u
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Screening for disease
❖ It has been defined as “search for
unrecognized disease or defect by means of
rapidly applied tests, examinations or other
procedures in apparently healthy individuals”.
Ex : Screening of tuberculosis
Syphilis
Antenatal mothers
School children
Occupational groups
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Screening -I
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Screening :
1) Capable of wide applications
2) Relatively inexpensive
3) Requires little physician time
4) An initial examination
5) Those who are positive, referred to
physician for further diagnostic tests
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Aims & objectives:
1) The purpose of screening is to sort out from a
large group of apparently healthy persons those
likely to have the disease or at increased risk of
disease under study.
2) To bring those who are apparently abnormal
under medical care and treatment
3) It is carried out to have early diagnosis &
treatment
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Screening : It is testing for infection or disease in the populations or in individuals who are not seeking health care – Ex :Serological tests for HIV/AIDS.
Neonatal screening
Premarital screening for syphilis
Case finding : Clinical or laboratory test to detect disease in individuals seeking health care for other reasons. Ex : VDRL test for syphilis in pregnant women.
Hypertensions.
Cervical cancer.
Diabetes.
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Diagnostic tests : Clinical or laboratory
procedures to confirm or refute the existence of
disease or true abnormality in the patients with
signs & symptoms presumed to be caused by the
disease. Ex : VDRL – testing – suggestive of
secondary syphilis.
Uses of screening : 1. Case detection :-
Ex : Bacteuria in pregnancy
Breast cancer
Cervical cancer
Diabetes
Iron deficiency anaemia
TB
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2. Control of disease – It is prospective
screening . Ex :-
1. Screening of immigrants from infectious
disease – ex : syphilis & TB
2. Screening of streptococcal infectious to
prevent rheumatic fever .
3. Research purpose
4. Educational opportunities
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❖ Types of screening :-
Three types
a) Mass screening – Ex – Mass screening TB
b) High risk or selective screening – Ex :-
1) Screening of lower social groups for cancer cervix
2) Elevated serum cholesterol to coronary heart disease.
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c) Multiphase screening – Applications of two or
more screening tests in combinations to a larger
number of people at one time than to carry out
separately.
Ex:-
1) Chemical & hematological tests on blood and
urine
2) Lung functions tests
3) Audiometry and measurement of visual acuity
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• Criteria for screening – It is based on twoconsiderations ie disease to be screened and test to beapplied
a) Disease – The disease should fulfill the following criteria.
1) The condition should be an important health problem(prevalence should be high).
2) Should be recognizable latent or early asymptomatic.
3) Natural history of the conditions should be adequatelyunderstood.
4) There is a test that can detect the disease prior to onsetof signs & symptoms.
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5) Facilities should be available for confirmation of the
diagnosis
6) There is a effective treatment
7) There should be an agreed –On policy concerning
whom to treat as patients. Ex : Lower range of blood
pressure border – line diabetes
8) There is a good evidence that early detection and
treatment reduces morbidity & mortality
9) The expected benefits of early detection
exceed the risk and costs
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❖ Screening tests – The test must satisfy the criteria of
acceptability, repeatability and validity with an yield,
simplicity, safety, rapidity, ease of administration and
cost.
1. Acceptability – In general tests may be painful,
discomfort or embracing.
2. Repeatability – The test must give consistent results
when repeated more than once on the same individual or
material, under the same conditions.
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Repeatability depends on three major factors:-
a) Observer variations :
1) Intra observer variations- Ex – BP, chest
measurements
2) Inter observer variations – The variations between
different observer on the same subject or material ex
– x-ray reading, ECG, BP.
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b) Biological variation- Associated with physiological
variables, blood pressure, blood sugar, S.cholesterol
➢ Changes in parameters - One site negative another
positive
➢ Variations in the recollection of past events
➢ Regression to the mean – Ex : BP, blood sugar
c) Errors relating to technical methods
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3) Validity (accuracy) – Validity expresses the ability of a test to
separate and distinguish those who have disease from those who
do not
Ex : glucose tolerance test for diabetes
• It got two components:
1) Sensitivity– The ability of a test to identify correctly all those who
have disease. true positives
2) Specificity – The ability of a test to identify correctly those who do
not have the disease: true negatives.
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❖Sensitivity and specificity determined by
applying the test to one group of person
having the disease, and to a reference
group not having disease.
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Disease+
Disease-
Test + 9 11
Test - 10 10
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❖Sensitivity – a /a + c x 100
❖Specificity – d / b + d x 100
❖Predictive value of a positive test = a / a + b x 100
❖Predictive value of a negative test = d / c + d x 100
❖Percentage of false negatives = c / a + c x 100
❖Percentage of false positives = b / b + d x 100
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❖Yield : It is the amount of previously unrecognized
disease that is diagnosed as a result of screening
effect. Ex : Diabetes after 40 yrs.
❖Combinations of tests – Syphilis screening – 1st
to RPR test, then we yield false positives - FTA –
ABS- more specificity test true syphilis
❖The problem of borderline case -
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Predictive accuracy :-
❖It will give the diagnostic power of the test.
❖It depends on sensitivity, specificity & disease
prevalence.
❖The predictive value of a positive test indicates
the probability that a patient with a positive test
❖More prevalence of a disease in population, the
more accurate the predictive value of a positive
screening test.
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➢False negative :- False negatives means that
patients who actually have the disease are told that
they do not have the disease.
➢The lower the sensitivity, the larger will be the
number of false negatives.
➢False positives : False positive means that they
patients who do not have the disease are told that
they have. A screening test with a high specificity
will have few false positives.
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Important points in screening test :-
1) It must be applied selectively to those
people most likely to benefit . Ex : -
Cervical cancer cytology
Age
Sex
Medical history
Occupation
Family history etc.
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➢ Evaluation of screening programmes :
1) RCT – When disease has low frequency with
long incubation period.
2) Uncontrolled trails – Ex : Cervical cancer pap
smear
3) Other methods:-
a) Case control studies
b) Comparison trends between areas.
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