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EXAM EPIDEMIOLOGY > Feldmand. Module 1 – Intro to Epidemiology & Measures of Disease > Flashcards

Feldmand. Module 1 – Intro to Epidemiology & Measures of Disease Flashcards

1
Q

Definition of epidemiology

A

• From Greek

  • – Epi (among, upon)
  • – Demos (the people)
  • – Logos (knowledge, doctrine)

• The study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to the control of health problems (Dictionary of Epidemiology)

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2
Q

Goals of Epidemiology

A
  • Elaboration of causes that explain patterns of disease occurrence
  • Determine extent of disease
  • Study natural history of disease
  • To promote, protect and restore health
  • Provide foundation for developing public policy and regulatory decisions
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3
Q

Typical Epidemiologic Approach

A
  • Determine existence and magnitude of problem
  • Describe WHO has the problem (animal/person, place, time)
  • Develop hypotheses about WHY problem is happening
  • Test the hypotheses using appropriate study designs and statistical tests
  • Develop interventions based on findings
  • Evaluate effectiveness of interventions
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4
Q

Basic Tenet of Epidemiology

A

• Disease does not occur randomly in a population

  • – Disease occurrence is related to environment of species being studied
  • – Environment includes physical, biological, sociological, meteorological, & management characteristics

• Epidemiology triad

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5
Q

Epidemiologic Triad

A

• Disease is result of forces within a dynamic interaction between

– Agent

– Host

– Environment

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6
Q

Measures of Disease: Ratios

A
  • An expression of the relationship of 2 quantities
  • Numerator is not in the denominator
  • With a dimension – # of dogs owned / 100,000 population
  • Without a dimension – # 2nd year vet students / # 3rd yr vet students
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7
Q

Measures of Disease: Proportions

A
  • Ratio in which numerator is contained in the denominator
  • Dimensionless
  • Ranges from 0 – 1
  • Tells us what fraction of population is affected

vets sitting ACVPM exam / Total # vets

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8
Q

Rates

A
  • Ratio in which there is a relationship between the numerator and the denominator
  • A true rate is instantaneous change in one quantity per unit change in another quantity (usually time).
  • Tells us how fast disease occurs in a population

tests taken in vet curriculum / person-years in vet curriculum

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9
Q

Measures of Morbidity: Prevalence

A

• Prevalence (point prevalence, prevalence rate) – Proportion of pop’n with disease at a specific time

of subjects with disease at a point in time / Population at the same point in time

• Period prevalence – Frequency of disease for a given time interval

of subjects with disease for given time interval / Population at mid-interval

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10
Q

Interpretation of prevalence

A

Probability of having disease at a particular point in time.

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11
Q

Measures of Morbidity: Cumulative incidence, incidence proportion

A

– Proportion of subjects who develop disease during a certain time period

– Unitless, interpret in the context of time period

– Measure of average risk for a population

events during a period of time / Population without disease at beginning of period

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12
Q

Measures of Morbidity: Incidence • Incidence rate, incidence density

A

– Occurrence of new event per unit time

– The numerical value has no interpretability because it depends on the arbitrary selection of the time unit

new events / Total person-time at risk in population

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13
Q

Measures of Morbidity: Incidence • Attack rate

A

– Cumulative incidence used for particular populations observed for limited periods of time, as in an outbreak

– Usually expressed as a percent

events of dz during epidemic time period / Population at risk at start of period

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14
Q

Interpretation of cumulative incidence

A

Risk of developing disease over given time period

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15
Q

Interpretation of incidence density

A

Rapidity with which new new cases develop over given time period

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16
Q

Relation between Prevalence, Incidence & Duration

A
  • Prevalence is not a measure of risk: Does not take into account the duration of the disease
  • If prevalence (P) is small and incidence rate (I) and duration (D) are constant over time then P ≈ IxD
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17
Q

Measures of Mortality

A
  • Mortality rate: Total # deaths from all causes in 1 year / Population at mid-year
  • Disease-specific mortality rate: Total # deaths from specific dz in 1 year / Population at mid-year
  • Case-Fatality Rate (CFR) # deaths after dz onset or diagnosis / # individuals with the dz
  • Proportionate Mortality # deaths from specific dz in time period / Total # deaths in that time period
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18
Q

Mortality: when can it be a good index of the risk of disease?

A

• Can indicate severity of disease and also be an index of the risk of disease

  • – If a disease is not typically fatal, mortality is not a good index of incidence • E.g., West Nile virus
  • – When the case fatality rate is high and duration of disease is short, mortality is good reflection of risk • E.g., Rabies
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19
Q

Risk

A
  • The probability of a disease-free individual developing a given disease over a specified period, conditional on that individual not dying from any other disease during the period
  • Risk is without units, ranges from 0 to 1
  • Risk=Attack rate in outbreak settings: # events of disease during time period / Population at risk at start of period
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20
Q

Odds

A

• The probability of an event occurring compared to the probability of that event not occurring

Probability event occurs / Probability event does NOT occur

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21
Q

2-by-2 tables

A

Disease Present Absent

Exposure +

Exposure -

Note that the disease status is across the top and the exposure status is on the left

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22
Q

(use of) Ratio Measures of Association

A
  • Assess the strength or magnitude of the statistical association between the exposure and disease of interest
  • In cohort studies, use relative risk
  • In case-control studies, use odds ratio
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23
Q

Identification of Risk Factors

A

Epidemiological studies are conducted to identify risk factors through the comparison of incidence or prevalence between groups exposed and not exposed to a risk factor.

Probabilities of disease occurrence can be compared using:

  • measures of strength of association: RR, OR
  • measures of potential impact: attributable risk, attributable fraction.
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24
Q

Measures of strength of association and information provided

A

Involves calculation of ratios such as relative risk and odds ratio which measure the magnitude of a statistically significant association between risk factor and disease.

They are used to identify risk factors, but do not provide information on absolute risk.

25
Q

Relative Risk (RR)

A
  • The relative risk is the excess risk in the exposed group, compared to the unexposed (background, expected group)
  • Expressed as a ratio
  • RR = Riskexposed / Riskunexposed
  • Riskexposed = # events of dz in exposed group / pop’n at risk in exposed group = a / (a + b) = a / h1
  • Riskunexposed = # events of dz in unexposed group / pop’n at risk in unexposed group = c / (c + c + d) = c/h2
  • RR = Riskexposed / Riskunexposed = (a/h1) / (c / h2)
  • The RR will be > 1.0 when risk is greater in the exposed group than in the unexposed group – i.e., when exposure is risk factor for disease
  • The relative risk will be <1.0 when risk in the exposed group is less than risk in the unexposed group – i.e., when exposure is protective
  • When no association between exposure and disease, RR = 1
26
Q

Odds Ratio (OR) - (type of studies to use, why)

A
  • In case-control studies, you cannot directly calculate the risk of disease because you do not have a denominator population
  • You can calculate the odds of exposure among cases and controls
  • The OR compares the odds of exposure in cases to the odds of exposure in controls
27
Q

Measures of Potential Impact: what are those and why are important

A
  • Reflect the apparent contribution of an exposure to the frequency of disease in a population
  • Important for policy makers and funding sources to understand impact a prevention program might have
28
Q

Measures of potential impact and information provided

A

Measures of potential impact include differences such as the attributable risk or fractions such as the attributable fraction.

These allow quantifying the consequences from exposure to a risk factor, and are used to predict, quantify the effect of prevention and to plan control programs

29
Q

Risk Difference

A

Measure of potential impact.

• Also called excess risk, attributable risk:

Risk Difference = Riskexposed – Riskunexposed

• Excess risk in those exposed

30
Q

Attributable Risk Percent

A
  • Only appropriate if RR > 1
  • Proportion of cases in the exposed group attributable to exposure
  • The most that we can hope to accomplish in reducing risk of disease if we completely eliminate the exposure

(Riskexposed – Riskunexposed) / Riskexposed = (RR – 1) / RR

31
Q

Population Attributable Risk Percent

A

• Proportion of cases in the entire population (exposed and unexposed) attributable to exposure

(Riskoverall – Riskunexposed) / Riskoverall

32
Q

Prevented Fraction in the Exposed - Vaccine Efficacy

A
  • Comparable measure to attributable risk percent for a protective factor, such as vaccination
  • Only appropriate if the RR<1.0
  • Proportion of potential new cases which would have occurred had the exposure been absent (the proportion of potential cases prevented by the exposure)
  • Prevented fraction in the exposed = (Riskunexposed - Riskexposed) / Riskunexposed = 1 - RR
33
Q

Formula for True Prevalence (from Apparent Prevalence)

A

TP = (AP + Sp - 1) / (Specificity + (Sensitivity - 1)

34
Q

Formulas to calculate PPV

A

PPV = a / (a + b)

PPV = TP / (TP + FP)

35
Q

Formulas to calculate NPV

A

NPV = d / (c + d)

NPV = TN / (TN + FN)

36
Q

Definition of infectivity

A

Ability of an agent to establish itself in a host (ID50 = numbers of agents required to infecto 50% of exposed susceptible animals under controlled conditions)

37
Q

Definition of pathogenicity

A

Ability of an agent to produce disease in a range of hosts under a range of environmental conditions

38
Q

Definition of virulence

A

Measure of the severity of disease caused by a specific agent. It is commonly quantified using the LD50 (= numbers of agents required to kill 50% of exposed susceptible population under controlled conditions)

39
Q

Definition of carrier state

A

A true carrier state is characterised by an infected host who is capable of dissemination of the agent, but typically does not show evidence of clinical disease.

40
Q

Definition of incubatory carrier

A

Incubatory carriers are infected, disseminate the agent but are in the pre-clinical stage.

41
Q

Definition of convalescent carriers

A

Convalescent carriers are infected, disseminate the agent and are in the post-clinical stage.

42
Q

Definition of antigenic variation

A

Refers to biological situations where an agent evades the host defence by changing its antigenic characteristics.

43
Q

Definition of incubation period

A

Defined as the time between infection and the first appeareance of clinical signs.

44
Q

Definition of period of communicability

A

Time during which the infected host is capable of transmitting the agent

45
Q

What is a natural reservoir of infection

A

A species is considered a natural reservoir of infection if infection can be maintained within the species population without requiring periodic re-introduction.

46
Q

Unified concept of causation criteria:

A

Developed by Evan, is accepted for identifying cause-effect relationships.

  • The proportion of individuals with the disease should be higher in those exposed to the cause than in those not exposed.
  • exposure to the cause should be more common in cases than in those without the disease
  • number of new cases should be higher in those exposed to the case than in those not exposed (as shown in prospective studies)
  • temporally, the disease should follow exposure to the cause
  • There should be a measurable biological spectrum of host responses
  • The host response should be repeatable following exposure to the cause
  • The disease should be reproducible experimentally
  • preventing or modifying the host response should decrease or eliminate the expression of disease
  • elimination of the cause shoud result in a lower incidence of the disease
  • the relationship should be biologically and epidemiologically plausible
47
Q

What are necessary and sufficient causes of disease?

A

Cause of disease can be categorised into:

  • necessary causes: must be present for a disease to occur (e.g. distemper virus in canine distemper)
  • sufficient causes: set of minimal conditions and events inevitably producing disease.
48
Q

False Negative Rate (β)

A

beta = type II error

beta = 1 - Se

beta = False Neg / (True Pos + False Neg)

49
Q

False Positive Rate (alpha)

A

alpha = type I error

alpha = 1 - Sp

alpha = False Pos / (False Pos + True Neg)

50
Q

Positive likelihood ratio calculation

A

Positive likelihood ratio (LR+) = Se / (1 - Sp)

[LR+ = True Pos Rate / False Pos Rate]

Interpretation: likelihood ratio for a positive test = 3 this means that a positive test (in this case PFL>=4) is 3 times more likely to come from an animal with disease (e.g. SL) than from an animal with NSL.

51
Q

Negative likelihood ratio calculation

A

Negative likelihood ratio (LR-) = (1 - Se) / Sp

[LR- = False Neg Rate / True Neg Rate]

52
Q

Accuracy calculation

A

ACC = (True Pos + True Neg) / Population

53
Q

Diagnostic Odds ratio (DOR)

A

DOR = LR+ / LR-

(positive likelihood ratio / negative likelihood ratio)

54
Q

calculation of True Positives (a) with prev and test parameters

A

True Pos = True Prev * Se

55
Q

calculation of False Positives (b) (with prev)

A

False Pos = (1 - True Prev) (1 - Sp)

56
Q

calculation of True Negatives (d) with prev and test parameters

A

True Neg = (1 - True Prev) * Sp

57
Q

calculation of False Negatives (c) with prev and test parameters

A

False Neg = True Prev * (1 - Se)

58
Q

Strategies for selection of an appropriate test to rule out disease and to find evidence of disease

A
  • If the objective of diagnostic testing is to rule out disease, it means that a reliable negative result is required and therefore the test should generate few false negatives (=high sensitivity).
  • In contrast, in order to find evidence (=rule in) of true disease and minimise false positive results, a reliable positive result is required with few false positives (=high specificity).
59
Q

Methods for choosing normal / abnormal criteria (i.e. criteria for deriving cut-off values)

A
  • Gaussian distribution method
  • percentile
  • therapeutic
  • risk factor
  • dianostic or predictive value
  • culturally desirable

EXAM EPIDEMIOLOGY (16 decks)

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