Veterinary Epidemiology and Economics II HDA

8/3/2019 Veterinary Epidemiology and Economics II HDA

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Veterinary Epidemiology and Economics IICLIS 722

3 (2+1)

Course outline

1. Diagnostic test Evaluation1.1 Diagnostic and gold standard tests

1.2 Sensitivity

1.2 Specificity

1.3 Test performance- Predictive value


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2.Herd level testing

2.1 Test Properties at individual level2.2 Test Properties at herd level

6.2.1 Herd level sensitivity6.2.2 Herd level specificity6.2.3 Detecting diseased herd

2.3 Predictive values of herd test

3. Standardization of rates3.1 Direct standardization

3.2 Indirect standardization


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4.Source and nature of epidemiological data3.1 Classification of data (Nominal, ordinal

interval)3.2 General requirement of epidemiological data3.3 Sources of data3.4 The sampling processes

3.5 using the existing data5.Questionnaire and participatory appraisal

5.1 Good practice in questionnaire design andimplementation

5.2 Good practice Verses actual practice in theuse of questionnaire survey

5.3 Why is participation is important?5.4 types of community participation5.5 Attitude and behaviour in participatory

epidemiology


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5.6 Participatory methods

5.7 Participatory disease searching: some

principles

5.8 Resource materials and organization for

participatory epidemiology


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Evaluation of Tests : Diagnostic and Screening

Introduction

Tests are used for diagnosis, screening, and research

How well is a subject classified into disease or non-

disease group? Ideally, all subjects who have thedisease should be classified as having the diseaseand vice versa

Practically, the ability to classify individuals intothe correct disease status depends on theaccuracy of the tests, among other things


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Introduction

A diagnostic test is used to determine the presenceor absence of a disease when a subject shows signs orsymptoms of the disease

A screening test identifies asymptomatic individuals

who may have the disease The diagnostic test is performed after a positive

screening test to establish a definitive diagnosis


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Factors influencing veterinary diagnosis (from Pfeiffer,1998)


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The difference between screening and diagnostic test

Screening for population (apparently healthy)

Diagnosis for individuals ( sick)

Screening usually done once (case finding)

Diagnostic test can be done many times Reason : diagnosis is determine by clinical status

where as reason for screening is independent ofclinical status

Screening test can be followed by confirmatorydiagnosis


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Screening test

The majority of national/zonal control programmesfor infectious diseases is based on detection ofinfected individual by screening test

screening tests can be done;-

- Occasional, Systematic, mass and selective

A good test should make it possible to locate all the

infected individuals and Only those individual s that are really infected errors of omission and commission can be there


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Important properties of a screening test

1. Screening is simple, inexpensive, and easily diffusedthrough the population.

2. The act of screening is safe and acceptable.

3. The screening test is reliable (dependability).

4. The screening test is accurate (no screening test isperfect

5. Help to identify disease early in a certain population6. thus enabling earlier intervention and management

in the hope to reduce mortality and suffering from

a disease


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Screening biasmedical terms

Lead time bias

Lead time is the period of time between thedetection of a disease condition by screening andwhen it ordinarily would have been diagnosed becauseof symptoms

individuals who are diagnosed by screening for deadlydisease will live longer from the time of diagnosisthan those who are diagnosed because of symptoms,

even if early treatment is ineffective (disease timevs. survival time)


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Length/time bias

A disease may be fast growing or slow growingScreening is more likely to find slow growing

conditions (fast growing will have alreadycaused symptoms at the time of screening)

Therefore, screening is more likely to detect

diseases with better prognosis (but the factthat screened individuals have betterprognosis is not related to screening itself)


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Gold standard test

It a test (method) definitely determines weatherdisease is present or not in a group of animals orabsent in another group of animals

Classify animals as diseased (D+) non diseased (D-)

It can be- bacterial culture- a series of tests- clinical sign (pathognomonic)

- Virus isolation- post-mortem finding of GIT parasites- haemoparasites in blood smears


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Gold standard test count

Pathognomonic tests

The detection of signs, substance, response, tissuechanges are absolute predictors of the presence ofdisease or disease causing agent

Example: positive culture of Brucella abortusfrommilk sample

Surrogate tests

Detects secondary changes , which are hoped topredict presence or absence of disease or diseaseagent

Example: testing milk for Ab of Brucella abortus


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Variation in Biologic Values

When a test that gives a quantitative value (optical density indirect ELISA) applied to a homogeneous group of animals

Some are infected while others are not, the result will look likethe histogram

Two sub population can easily be identified based on OD reading

Sub-population I, with low test result, probably represent thoseanimals that are not infected.

OpticalDensity

Number

II

I


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Variation in Biologic Values cout..

Sub-population II, with high test result , must bemainly composed of infected animals, but

The distribution is continuous: There is not, on one hand , a group of animals for

which OD is low, which are all disease free Again on the other hand another group ,composed of

animals with high OD values, consisting of infectedanimals

This kind of perfect separation is almost impossible inmost of ever obtained tests In other word it is obviously not easy to determine

the Cut-off point


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Cut-off points in a screening test

There are two population distributions, the diseased and non-

diseased ,and they overlap on the measure of interest


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An intermediate zone exist , in which there are OD valuesrepresent either infected or non-infected animals (overlappingarea)

Both infected and non-infected animals can in the enclosing

values of OD that lie between , as a result

Thus there is always a risk that false result will be obtained whenusing a test,

The animals can be wrongly characterized as false positives andfalse negatives by a given test

The relative frequency of FP and FN determines the quality of atest


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False negative and False positive Results

False negative (FN)

Individual which are infected , and wrongly consideredas negative results by a given test This can be happen due to many reasons (from Stipes

et al. 1982).- natural and induced tolerance to antigens (BVD)

- improper timing (for sample collection)- improper selection of tests- non specific inhibitors (contaminated sera)- some chemicals suppress induction of

immunoglobulins- incomplete Ab-blocking of Ab (Excess IG1 blocks IG2)- Insesitive tests: lack of analytical sensitivity


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False negative and False positive Results

False positive (FP) individuals which are not infected and wrongly considered as

positive results by the test

Reasons for such a result could be associated with (from

Stipes et al. 1982).- crossrecations- non specific aglutinin- contamination during culture- non-specific inhibitors

These categories of errors can be shown in a table comparing thetrue situation, as it revealed by reference or Gold standardtest, which is assumed to be perfect


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The 2 by 2 table

it is a tool for evaluation of standardized screening

test, which predict the presence or absence ofdisease


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Validity

An important way to evaluate, view and analysis ofdiagnostic and screening tests (Validity)

Validity is the extent to which a test measure what

it was designed to measure

The most common indicators of validity of a test are- Sensitivity- Specificity

- Predictive values- efficiency


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Sensitivity and Specificity

Sensitivity The ability of the test to identify correctlythose who have the disease

Specificity The ability of the test to identify correctlythose who do not have the disease

Sensitivity:-probability by which a diseased animal is identified by the test as

positive- The proportion of true positives that are detected by the test- The ability of a test to correctly identify an infected individualSpecificity-it is the proportion of non-infected individuals for whom a

negative test result obtained-The proportion of true negative that are detected by the test


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Determining the Sensitivity, Specificity of a Test

FPTP

FN TN


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Sensitivity

= TP/(TP+FN)

Specificity

= TN/(FP + TN)


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False Positive Rate

Probability by which an animal is identified as testpositive (T+) while in fact it is non-diseased (D-)

False Negative Rate

Probability by which an animal is identified as test(T-) while in fact it is diseased (D+)


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Efficiency of test( accuracy)

It is the probability of a test to classify correctlyinfected and non-infected individuals of a studypopulation with a given prevalence

Likelihood ratio of positive test

the ratio of probability of a positive test, given the

disease, to the probability of a positive test, given nodisease,


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Likelihood ratio of negative test

negative test, given disease versus negative test, givenno disease


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Predictive values of a test

Positive Predictive Value

The probability that an animal is truly (actually)diseased when its test is positive

PV+ = P(D+/T+) = P(D+ and T+)/P(T+)

Negative Predictive Value

The probability that an animal is truly (actually) non-diseased when its test is negative

PV- = P(D-/T-) = P(D- and T-)/P(T-)


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Applying Concept of Sensitivity and Specificity to aScreening Test

Assume a population of 1,000 people 100 have a disease

900 do not have the disease

A screening test is used to identify the 100 people

with the disease The results of the screening appears in this table

Evaluate the Validity of the screening test


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Applying Concept of Sensitivity and Specificity to aScreening Test

Their relationship with cut-off point The Cut-off point of a screening test has an effect on the

sensitivity and specificity of the test

Different cut-points yield different sensitivities andspecificities

The cut-point determines how many subjects will beconsidered as having the disease

The cut-point that identifies more true negatives willalso identify more false negatives

The cut-point that identifies more true positives willalso identify more false positives

Sensitivity and specificity are inherentcharacteristics of a test


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Their relationship with cut-off point count.

A low cut-off point is chosen , if it is to avoid FN

If is to avoid FP use A high cut-off point

Where to draw the cut points ?

If the diagnostic (confirmatory) test is expensive or invasive:Minimize false positives or Use a cut-point with high specificity

If the penalty for missing a case is high (e.g., the disease isfatal and treatment exists, or disease easily spreads): Maximize true positives, That is, use a cut-point with high

sensitivity

In a mass screening test for a less serious condition or forone where early detection is not critical, it may be moredesirable to have a high specificity ( low cut-off point)

Balance severity of false positives against false negatives


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The relationship between sensitivity and specificity

Sensitivity and specificity are inversely related This is because the measured characteristics (Ab) by

the test are present in diseased as well as in non-diseased animals, although in different sizes and

magnitude in each group and distribution of substancewill frequently overlap

The differences between specificity and sensitivityof two diagnostic tests for purpose of comparingtheir validity and effectiveness can be done by

ROC (Receiver Operating Chrematistic) curve


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ROC (Receiver Operating Chrematistic) curve

This curve will be constructed by plotting the true positive rate(sensitivity) in Y-axis against its corresponding false positive rate (1-Specificity) on X-axis

We are able to select the more accurate of the two test by selectingthe curve that lies closer to the upper left hand corner of the Graph.

(sen =1, 1-sep =0)


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Applying Concept of Predictive Values to Screening Test

For a diagnostic decision, it is also useful to make

some estimate of the predictive value of a diagnostictest

This requires knowledge of the sensitivity andspecificity of the test and the prevalence of the

condition The effect of prevalence on predictive values isconsiderable.

As prevalence increases, Positive Predictive Value

(PPV) increases and Negative Predictive Value (NPV)decreases.

PPV and NPV are not fixed values

PPV, depends more on the specificity (and less on the

sensitivity) of the test (if the disease prevalence islow


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Applying Concept of Predictive Values to Screening Test

Relationship of Disease Prevalence to Predictive Value


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Adapted from Mausner JS, Kramer S.Epidemiology: anIntroductory Text. Philadelphia, WB Saunders 1985,

p221


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Veterinary Epidemiology and Economics II HDA

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