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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.

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Definition l.jpg
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


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Epidemiological approaches l.jpg

Environment health and disease in populations

Model

of Disease

Host

Agent

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


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Epidemiological Approaches health and disease in populations

  • Etiologic Epidemiology

    • Determining the cause of disease

    • “Medical detection” epidemiology

    • “Shoe leather” epidemiology

    • Outbreak investigation


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Epidemiological Approaches health and disease in populations

  • Clinical Epidemiology

    • Answers questions asked in practice of veterinary and human medicine

      • Normality/Abnormality

      • Diagnosis

      • Frequency

      • Risk/Prevention

      • Prognosis

      • Treatment

      • Cause


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Epidemiological Approaches health and disease in populations

  • Quantitative Epidemiology

    • Mathematically describe diseases and associated factors

    • Explore potential “cause and effect” associations


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Epidemiological Approaches health and disease in populations

  • 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


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Application of Epidemiology health and disease in populations

  • 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.


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Environment health and disease in populations

Model

of Disease

Host

Agent

Ecology of Disease


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Environment health and disease in populations

Host

Agent

Ecology of Disease

Model

of Disease


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Environment health and disease in populations

Host

Agent

Ecology of Disease

Model

of Disease


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Model of Disease health and disease in populations

  • Agent

    • A factor whose presence is required for the occurrence of a disease.


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Model of Disease health and disease in populations

  • Host

    • Animal that supports the replication or development of an agent or is affected by an agent under natural conditions.


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Genotype health and disease in populations

Age

Sex

Species and Breed

Nutritional status

Immune status

Size and Conformation

Coat Color

Host Determinants


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Model of Disease health and disease in populations

  • Environment

    • Physical surroundings and management factors that affect hosts and agents


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Environmental Determinants health and disease in populations

  • Location

  • Climate

    • Macroclimate

    • Microclimate

  • Management

    • Housing

    • Diet

    • Husbandry – density, pig-flow, etc.


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Model of Disease health and disease in populations

  • Changes in relationships result in different outcomes

    • Agent overcomes host

    • Host overcomes agent

    • Agent and host maintained in equilibrium


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Measuring and Expressing Occurrence of Disease health and disease in populations

  • 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


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Measuring and Expressing Occurrence of Disease health and disease in populations

  • Pandemic

    • An epidemic that occurs over a large geographical area or the world


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Measuring and Expressing Occurrence of Disease health and disease in populations

  • Outbreak

    • Localized epidemic


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Measuring and Expressing Occurrence of Disease health and disease in populations

  • Endemic

    • Occurrence of disease at a constant or expected level


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Measuring and Expressing Occurrence of Disease health and disease in populations

  • Sporadic

    • Pattern of disease in which the disease occurs rarely and without regularity


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Frequency of Clinical Events health and disease in populations

  • Mathematically describing occurrence of events such as disease and death

    • Rates

    • Ratios

    • Proportions


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Number of Cases health and disease in populations

Prevalence =

Total Number of Animals

Frequency of Clinical Events

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


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No. of new cases over a time period health and disease in populations

Incidence Rate =

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

Frequency of Clinical Events

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


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Frequency of Clinical Events health and disease in populations

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


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Frequency of Clinical Events health and disease in populations

  • 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


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Frequency of Clinical Events health and disease in populations

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


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Frequency of Clinical Events health and disease in populations

  • 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


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Frequency of Clinical Events health and disease in populations

  • Factors Affecting Incidence and Prevalence

    • Temporal Sequences

    • Disease Duration

    • Case Definition

    • Dangling Numerators

    • Population at Risk

    • Crude vs Adjusted Rates

    • Real vs Apparent Prevalence


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Factors Affecting health and disease in populations 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


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Test Outcomes health and disease in populations


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a+c health and disease in populations

n

True Prevalence =


Apparent prevalence l.jpg

a+b health and disease in populations

n

Apparent Prevalence =


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Accuracy health and disease in populations

  • How close is a test result to the truth

  • Proportion of all tests, both positive and negative, that are correct


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a+d health and disease in populations

n

Accuracy =


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What is Truth? health and disease in populations

  • Gold Standard

    • The test that is used todetermine if a disease is truly present or not


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What is Truth? health and disease in populations

  • Gold Standard

    • The test that is used todetermine if a disease is truly present or not

    • Other tests are compared to it to determine their accuracy


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Test (Diagnostic) Sensitivity health and disease in populations

  • 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


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a health and disease in populations

a+c

Sensitivity =


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Sensitivity health and disease in populations

False Negatives

False Negative Rate

  • Likelihood of a negative result when patient actually has disease


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False Negatives health and disease in populations

Sensitivity

False Negative Rate

  • Likelihood of a negative result when patient actually has disease


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False Negatives health and disease in populations

Sensitivity

False Negative Rate

  • False negative rate increases with decreased sensitivity

  • Likelihood of a negative result when patient actually has disease


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Reasons for health and disease in populations 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


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Test (Diagnostic) Specificity health and disease in populations

  • 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


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d health and disease in populations

b+d

Specificity =


False positive rate l.jpg

Specificity health and disease in populations

False Positives

False Positive Rate

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


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False Positives health and disease in populations

Specificity

False Positive Rate

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


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False Positive Rate health and disease in populations

  • False positive rate increases with decreased specificity

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

False Positives

Specificity


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Reasons for health and disease in populations False Positive Reactions

  • Cross-reaction

  • Non-specific inhibitors

  • Non-specific agglutinins

  • Contamination


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Relationship of health and disease in populations Sensitivity and Specificity

Nondiseased

Diseased


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Critical Titer health and disease in populations

Nondiseased

Diseased


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Critical Titer health and disease in populations

Nondiseased

Diseased

False Negatives


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Critical Titer health and disease in populations

Nondiseased

Diseased

False Negatives

False Positives


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Increased Sensitivity – Decreased Specificity health and disease in populations

Critical Titer

Nondiseased

Diseased

False Negatives

False Positives


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Decreased Sensitivity – Increased Specificity health and disease in populations

Critical Titer

Nondiseased

Diseased

False Negatives

False Positives


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Predictive Value of a Positive Test health and disease in populations

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

  • Dependent upon:

    • Sensitivity

    • Specificity

    • Prevalence


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a health and disease in populations

a+b

Predictive Value(+) =


Slide60 l.jpg
Effect of prevalence on positive predictive value when sensitivity and specificity of a test equal 95%


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Predictive Value of a Negative Test sensitivity and specificity of a test equal 95%

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

  • Dependent upon:

    • Sensitivity

    • Specificity

    • Prevalence


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d sensitivity and specificity of a test equal 95%

c+d

Predictive Value(-) =


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


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Establishing Cause of Disease sensitivity and specificity of a test equal 95%

  • 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


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Establishing Cause of Disease sensitivity and specificity of a test equal 95%

  • 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


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Establishing Cause of Disease sensitivity and specificity of a test equal 95%

  • 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


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Measures of Association sensitivity and specificity of a test equal 95%

  • 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 l.jpg

a/(a+b) sensitivity and specificity of a test equal 95%

c/(c+d)

Relative Risk =


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Measures of Association sensitivity and specificity of a test equal 95%

  • 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 l.jpg

a/b sensitivity and specificity of a test equal 95%

ad

c/d

bc

Odds Ration = =


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Measures of Association sensitivity and specificity of a test equal 95%

  • 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


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Attributable Risk = sensitivity and specificity of a test equal 95%

a/(a+b) -

c/(c+d)


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Statistical Significance sensitivity and specificity of a test equal 95%

  • A strong association between a factor and a clinical event does not prove causality

    • Confounding with an unknown factor

    • Insufficient sample size


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Summary sensitivity and specificity of a test equal 95%

  • 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


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