Robert W. Wills, DVM, PhD Diplomate ACVPM (Epidemiology) Pathobiology and Population Medicine...

Robert W. Wills, DVM, PhDDiplomate ACVPM (Epidemiology)

Pathobiology and Population MedicineCollege of Veterinary Medicine

Mississippi State University

Epidemiology Overview and Concepts

Definition

Epidemiology Greek

Epi – about or upon Demos – populace or people of districts Logos – word Study of that which is upon the people The study of disease in populations

Study of the frequency, distribution, and determinants of health and disease in populations Analogous to pathogenesis of disease in individuals Epidemiology is a fundamental science for medicine in

populations.

Martin et al., 1987

Epidemiological Approaches

Ecological Epidemiology Medical Epidemiology Understanding how disease

agents are transmitted and are maintained in environment

Life cycle or natural history of disease

Foundation for disease eradication programs

Environment

AgentHost

Model of Disease


Etiologic Epidemiology Determining the cause of disease “Medical detection” epidemiology “Shoe leather” epidemiology Outbreak investigation


Clinical Epidemiology Answers questions asked

in practice of veterinary and human medicine Normality/Abnormality Diagnosis Frequency Risk/Prevention Prognosis Treatment Cause


Quantitative Epidemiology Mathematically describe diseases and associated

factors Explore potential “cause and effect” associations

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Preventive Medicine Design optimal management, control or

preventive strategies Use all available epidemiological approaches

to accomplish this Cost-effectiveness or cost-benefit is important

component

Application of Epidemiology

It integrates well with basic science by testing the application of experimental

models in the real world by discovering relationships between

outcomes and risk factors which may generate hypotheses for mechanisms of disease.

Ecology of Disease

Environment

Agent

Model of Disease

Host

Ecology of Disease

Model of Disease

Environment

Agent Host

Model of Disease

Agent A factor whose presence is required for the

occurrence of a disease.

Model of Disease

Host Animal that supports the replication or

development of an agent or is affected by an agent under natural conditions.

Host Determinants

Genotype Age Sex Species and

Breed

Nutritional status Immune status Size and

Conformation Coat Color

Model of Disease

Environment Physical surroundings and management

factors that affect hosts and agents

Environmental Determinants

Location Climate

Macroclimate Microclimate

Management Housing Diet Husbandry – density, pig-flow, etc.

Model of Disease

Changes in relationships result in different outcomes Agent overcomes host Host overcomes agent Agent and host maintained in equilibrium

Measuring and Expressing Occurrence of Disease

Epidemic An increase in the number of subjects affected

by a disease over the EXPECTED rate of occurrence

Epizootic Term used to express an epidemic in a

population of animals


Pandemic An epidemic that occurs over a large

geographical area or the world


Outbreak Localized epidemic


Endemic Occurrence of disease at a constant or

expected level


Sporadic Pattern of disease in which the disease occurs

rarely and without regularity

Frequency of Clinical Events

Mathematically describing occurrence of events such as disease and death Rates Ratios Proportions


Prevalence – Proportion of animals within a population that have a condition of interest at a given point in time

Prevalence =Number of Cases

Total Number of Animals


Incidence Rate – Proportion of animals that develop a condition of interest over a specific period of time

Incidence Rate =No. of new cases over a time period

Average population at risk during time period (e.g. animal-months)


Prevalence represents the risk of being a case, whereas incidence represents the risk of becoming a case (Smith, 1995)


Morbidity rate – As measure of prevalence

Proportion of animals that are affected with disease at a point in time

As measure of incidence Number of new cases of disease that occur in the

average population at risk during a specified time period


Mortality rate – Number of animals that die during a period of time


Attack rate Special kind of incidence rate Numerator is the number of new cases Denominator is the number of individuals

exposed at the START of an outbreak Of the individuals exposed to an agent, how

many acquired the disease


Factors Affecting Incidence and Prevalence Temporal Sequences Disease Duration Case Definition Dangling Numerators Population at Risk Crude vs Adjusted Rates Real vs Apparent Prevalence

Factors Affecting Incidence and Prevalence

Real vs Apparent Prevalence No test is 100% accurate Tests give us apparent prevalence not the

true prevalence Need to know the sensitivity and specificity

of the test to calculate true prevalence

Test Outcomes DISEASE

Present Absent

Positive a

True Positive

b False

Positive a+b

TEST

Negative c

False Negative

d True

Negative c+d

a+c b+d n

DISEASE

Present Absent

Positive a b a+b TEST RESULT

Negative c d c+d

a+c b+d n

na+c

True Prevalence =

Apparent Prevalence =

DISEASE

Present Absent

Positive a b a+b TEST RESULT

Negative c d c+d

a+c b+d n

na+b

Accuracy

How close is a test result to the truth Proportion of all tests, both positive and

negative, that are correct

Accuracy = n

a+d

DISEASE

Present Absent

Positive a

True Positive

b False

Positive a+b

TEST

Negative c

False Negative

d True

Negative c+d

a+c b+d n

What is Truth?

Gold Standard The test that is used to

determine if a disease is truly present or not

What is Truth?

Gold Standard The test that is used to

determine if a disease is truly present or not

Other tests are compared to it to determine their accuracy

Test (Diagnostic) Sensitivity

Ability to correctly detect diseased animals

Not the same as analytical sensitivity which denotes the detection limits of a test

100-200 KNOWN diseased animals needed to establish diagnostic sensitivity

Sensitivity = a+c

a

DISEASE

Present Absent

Positive a

True Positive

b False

Positive a+b

TEST

Negative c

False Negative

d True

Negative c+d

a+c b+d n

False Negative Rate

Likelihood of a negative result when patient actually has disease

False Negatives

Sensitivity

False Negative Rate


False NegativesSensitivity

False Negative Rate

False negative rate increases with decreased sensitivity

Sensitivity

False Negatives


Reasons for False Negative Reactions

Natural or induced tolerance Improper timing Improper selection of test Analytically insensitive tests Non-specific inhibitors e.g. anticomplementary

serum; tissue culture toxic substances Antibiotic induced immunoglobulin suppression Incomplete or blocking antibody

Test (Diagnostic) Specificity

Ability to correctly detect non-diseased animals

Not just analytical specificity ability to measure the correct substance

2000 KNOWN non-diseased animals needed to establish

Specificity = b+d

d

DISEASE

Present Absent

Positive a

True Positive

b False

Positive a+b

TEST

Negative c

False Negative

d True

Negative c+d

a+c b+d n

False Positive Rate

Likelihood of a positive result when patient does not have the disease

False Positives

Specificity

False Positive Rate


False PositivesSpecificity

False Positive Rate

False positive rate increases with decreased specificity

Specificity

False Positives


Reasons for False Positive Reactions

Cross-reaction Non-specific inhibitors Non-specific agglutinins Contamination

0

5

10

15

20

25

30

35

40

Titer

Rel

ativ

e F

req

uen

cy

Nondiseased

Diseased

Relationship of Sensitivity and Specificity

0

5

10

15

20

25

30

35

40

Titer

Rel

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req

uen

cy

Critical Titer

Nondiseased

Diseased

0

5

10

15

20

25

30

35

40

Titer

Rel

ativ

e F

req

uen

cy

Critical Titer

Nondiseased

Diseased

False Negatives

0

5

10

15

20

25

30

35

40

Titer

Rel

ativ

e F

req

uen

cy

Critical Titer

False Positives

Nondiseased

Diseased

False Negatives

0

5

10

15

20

25

30

35

40

Titer

Rel

ativ

e F

req

uen

cy

Critical Titer

False Positives

Increased Sensitivity – Decreased Specificity

DiseasedNondiseased

False Negatives

0

5

10

15

20

25

30

35

40

Titer

Rel

ativ

e F

req

uen

cy

Critical Titer

False PositivesFalse Negatives

Decreased Sensitivity – Increased Specificity

Nondiseased

Diseased

Predictive Value of a Positive Test

Probability that an animal which is positive, according to the test, is actually positive

Dependent upon: Sensitivity Specificity Prevalence

Predictive Value(+) =

DISEASE

Present Absent

Positive a

True Positive

b False

Positive a+b

TEST

Negative c

False Negative

d True

Negative c+d

a+c b+d n

a+ba

Effect of prevalence on positive predictive value when sensitivity and specificity of a test equal 95%

Prevalence (%) Positive Predictive Value (%) 50.0 95.0 5.0 50.0 2.0 27.9 1.0 16.1 0.1 1.9

Predictive Value of a Negative Test

Probability that an animal which is negative according to the test is actually negative

Dependent upon: Sensitivity Specificity Prevalence

Predictive Value(-) = c+dd

DISEASE

Present Absent

Positive a

True Positive

b False

Positive a+b

TEST

Negative c

False Negative

d True

Negative c+d

a+c b+d n

Effect of prevalence on negative predictive value when sensitivity and specificity of a test equal 95%

Prevalence (%) Negative Predictive Value (%)

1 100

10 99

50 95

75 86

90 68

Establishing Cause of Disease

Koch’s Postulates (1882) Organism must be present in every case of the

disease Organism must be isolated and grown in pure

culture Organism must, when inoculated into a

susceptible animal, cause the specific disease Organism must then be recovered from the

animal and identified


Limitations of Koch’s Postulates Multiple etiologic factors Multiple effects of a singe cause Asymptomatic carriers Non agent factors such as age Immunologic processes as cause of disease Host-agent, host-environment interactions Noninfectious causes of disease


Temporal relationship between cause and effect Strength of association Dose-response relationship Biological plausibility Consistency of multiple studies Rule out other possible causes Reversible associations

Measures of Association

Relative Risk Quantifies the association of a factor with a

disease by comparing the incidence rate in a population with the factor to the incidence rate in a population without the factor

It gives an estimate of the strength of association between a factor and a disease

A relative risk of 1 indicates there is no increased risk

Relative Risk = c/(c+d)a/(a+b)

DISEASE

Present Absent

Present a b a+b FACTOR

Absent c d c+d

a+c b+d


Odds Ratio Measure of the association of a risk factor with

disease by comparing the odds of having a disease in a population with the factor to the odds of having a disease in a population without the factor

Can be used in case control studies where the size of the population at risk, and therefore incidence, is not known

Good estimate of relative risk if disease is relatively infrequent

Odds Ration = =c/d

a/b

bc

ad

DISEASE

Present Absent


Absent c d c+d

a+c b+d


Attributable Risk Additional incidence of disease attributable to

the risk factor itself Calculated by subtracting the incidence of

disease in a population not exposed to a factor from the incidence of disease in a population exposed to the factor

Provides a measure of the magnitude of the effect of a factor

Attributable Risk = c/(c+d)a/(a+b) -

DISEASE

Present Absent


Absent c d c+d

a+c b+d

Statistical Significance

A strong association between a factor and a clinical event does not prove causality Confounding with an unknown factor Insufficient sample size

Summary

When studying disease, many factors and relationships must be considered.

Typically, as researchers, we separate out certain components and look at them independently.

Simulation modeling has the potential to incorporate as many factors as we can recognize and develop a more holistic view

Robert W. Wills, DVM, PhD Diplomate ACVPM (Epidemiology) Pathobiology and Population Medicine...

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