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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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Variation in Biologic Values cout..
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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Variation in Biologic Values cout..
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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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