Principles of Epidemiology Epidemiology • Epidemiology is an old lineage born with man. Adem, Eve, and the Apple • Slow progress over time. • Rapid progress during the last four

1

Principles of Epidemiology

Dr Mustafa Sagri

Zawia medical college

Community medicine department

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.

2

Epidemiology

• Infectious diseases epidemiology

• Chronic diseases epidemiology

• Clinical epidemiology

• Malaria epidemiology

• Cancer Epidemiology

• ect ….

3

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

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?

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.

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

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

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

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

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

11

Anatomy of the definition

1) Study.

2) Distribution.

3) Determinants.

4) health related states.

5) Population.

6) Control.

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1)Study.

It based principles of Statistics & research methodology

13


2) Distribution.

by Disease. Triad (time, person & place)

When, where and who ???? (descriptive studies)

14


3) Determinants.

Causes or risk factors, how?? and why??

(analytic studies)

15


4) Health related states.

The whole spectrum of health status.

Infectious diseases

ND’s

Risks factors: smoking, life-style, obesity ect ..

16


5) Population.

The whole or groups rather than individuals.

Base for calculation (denominatio)

17


6) Control.

Developing & evaluating interventions to control.

Control stages

➢ Control

➢ Elimination

➢ Eradication

18

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

19

The Scope of Epidemiology

in detail

1) To study historically the rise & fall of

disease in population:

e.g. epidemics, fluctuation, changes and trends

20


in detail

2) Community diagnosis:

Health problems in terms of morbidity and

mortality.

Understanding of social & behavioural patterns

21


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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in detail

4) Evaluation of individual’s risks & chances.

Besides incidences and prevalences one can calculates odds ratios, risk factors, and attributable risks

23


in detail

5) Syndrome identification

by observing frequently associated findings in

individual patients, e.g., CRS & AIDS.

24


in detail

6) Describing the natural history of a disease.

Prepathogenesis & pathogenesis

25


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.

26

Epidemiological Methods

Epidemiologic Study

Designs

Epidemiologic Study Designs

Grimes & Schulz, 2002 (www)

Longitu

dinal

study

http://dx.doi.org/10.1016/S0140-6736(02)07283-5

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

Descriptive Epidemiology

• First phase of an epidemiological

investigation.

• When?? ------ Time distribution

• Where?? ------ Place distribution

• Who?? ------ Person distribution

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

I. Defining the Population

• In terms of total number

• In terms of

– Age

– Sex

– Occupation

– Cultural characters

It provides denominator for calculating rates

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.

34

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

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

Three kinds of time trends or fluctuations:

I Short – term fluctuations

II Periodic fluctuations

III Long term - fluctuations

Time Distribution

37

Time distribution - Uses

• Take appropriate action

• Know whether interventions are effective

• Develop hypothesis regarding the source

or cause of outbreak

38

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

40

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

41

Person distribution - age

• Almost every health related event vary

with age

– Measles

– Cancer

– Hypertension

42

Person distribution (sex)

• Distribution of disease varies between

males and females

43

Person distribution – other attributes

• Race

• Ethnicity

• Nationality

• Behaviour

• Socioeconomic groups

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).

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.

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.

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.

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.

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.

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.

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.

Analytical Epidemiology

Epidemiologic Study Designs

Grimes & Schulz, 2002 (www)

Longitu

dinal

study

http://dx.doi.org/10.1016/S0140-6736(02)07283-5

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


• 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


• 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?

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.,

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

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

Design of Case Control study

a b

c d

a+c b+d

Cases

(Disease +)

Control

(Disease -)

Risk factor +

Risk factor -

Steps in a Case Control study

• Selection cases and controls

• Matching

• Measurement of exposure to risk factor

• Analysis and interpretation

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

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

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

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

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.

Analysis

• Calculate exposure rates among cases

and controls

• Calculate the disease risk associated with

exposure (Odds ratio)

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’

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)

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’

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

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?

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

Analysis

CC study - advantages

• Easy to conduct

• Inexpensive

• No risk to people

• No attrition (loss of patients) problems

• No ethical problems

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

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)

Cohort study

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

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

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

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

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 -

Elements of a Cohort study1. Selection of study subjects

2. Selection of comparison (control) group

3. Data collection and Follow-up

4. Analysis

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

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.

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

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

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)

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

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

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

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

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

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

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)

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

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

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

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

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)

THANK YOU

../8/2018Intervention studies104

Study designs: Intervention trials

Principles of Epidemiology for Public Health (EPID600)


Topics for this lecture

• Experimental and observational

epidemiologic study designs

• Types of intervention trials

• Methodological issues

• Ethical issues


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

Intervention studies107

Analytic study designs

• Intervention trials (experimental)

• Cohort studies (observational)

• Case-control studies

(observational)

• Cross-sectional studies

(observational)


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



Example of a prevention trial:

Perinatal

transmission

of HIV

(ACTG 076)

NEJM 11/3/1994;

331(18):1173-1180

../8/2018110

Randomized trial experience

Photography for Quit for Life: Pinderhughes Photography (New York, NY),

Design: Advertising and Communications, Inc. (Durham, NC)


randomized trial experience



The distinction between therapeutic

and preventive is not always a

clear one

Examples:

Community trials of STI treatment



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)



• Intervention randomly assigned

• Intervention not randomly

assigned

Randomization is a key feature


Randomization

Why is randomized assignment of

intervention so important?


Why is randomized

assignment of intervention so

important?

Randomization is so important

because overall, it provides the

strongest evidence for causal

inference


Why is randomized


important?1. Best assurance that control group

(unexposed) is a valid substitute

population (avoids self-selection of

exposure)


Why is randomized


important? 1. Best assurance that control group


population

2. Only way to control for unknown

factors


Why is randomized


important?1. Best assurance that control group


population

2. Only way to control for unknown

factors

3. Facilitates masking of exposure status


1. Best assurance that control group (unexposed) is a valid substitute population

2. Only way to control for unknown factors


4. Avoids ambiguity of time order of

exposure and outcome (most intervention

studies achieve this)

Why is randomized


important?


Why is randomized


important?1. Best assurance that control group (unexposed)

is a valid substitute population

2. Only way to control for unknown factors


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


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?


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.”

Thank u

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

Screening -I

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

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

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.

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

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

❖ 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.

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

• 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.

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

❖ 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.

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.

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

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.

❖Sensitivity and specificity determined by

applying the test to one group of person

having the disease, and to a reference

group not having disease.

Disease+

Disease-

Test + 9 11

Test - 10 10

❖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

❖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 -

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.

➢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.

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.

➢ 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.

Documents

Principles of Epidemiology Epidemiology • Epidemiology is an old lineage born with man. Adem, Eve, and the Apple • Slow progress over time. • Rapid progress during the last four