Epidemiology Flashcards

1
Q

Epidemiology:

A

The study of distribution and determinants of health-related states or events in specified populations and the application of this study to the control of health problems

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Descriptive Studies:

A

Describe the ocurrence and distribution of one or more variables in a population, group, or sample
Ex: Rabies by species

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Analytical Studies:

A

Measure the relationship or association between two variables, usually a risk factor (or exposure) and an outcome
Ex: Rabies positivity rate in cats/dogs

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Questions asked by descriptive studies:

A

Who gets sick and who doesn’t?
Where?
When?
How are cases connected?
How big is the problem?

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Questions asked by analytical studies:

A

Why did this occur?
What can we do?

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Determinants:

A

Host
Agent
Environments

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Types of population data:

A

Measurement (quantitative)
Count (Categorical/Qualitative)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Examples of measurement data:

A

Weight, Hematocrit, BUN, Age, Survival Time, Titer, etc

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Count data examples:

A

Breed, Sex, +/-, Old/Young, Healthy/Sick/Dead

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Incidence answers what question?

A

What is the rate of occurrence of new cases?

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Prevalence answers which question?

A

What proportion of animals are sick at once

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Prevalence Calculation:

A

All Current Cases/Population at Risk

At a point in time

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Incidence calculation :

A

NEW cases/Population at Risk

During a specific time interval

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Primary Prevention:

A

An action that PREVENTS disease in healthy animals

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Secondary prevention:

A

Identifying animals with disease to prevent symptoms

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Tertiary Prevention:

A

Prevention of complications in animals who have the disease

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

P-Value:

A

Probability that a difference of this size or large would be observed it there really was no difference between groups (probability of this happening randomly)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

Significant P-Values:

A

<0.05

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

What answers the question “could the difference we found between the means be just due to chance variation?”

A

P-value

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

What answers the question “how certain are we of the size of the difference between the means?”

A

Confidence Interval

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

What answers the question “what is the rate of occurrence of new cases?”

A

Incidence

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

Case Fatality Calculation

A

Death among cases/total cases

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

What answers the question “What proportion of animals are sick at once?”

A

Prevalence

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

What answers “what proportion of cases die?”

A

Case Fatality Rate

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
Risk Ratio/Relative Risk:
Incidence w/ risk factor/incidence w/o risk factor
26
Risk Difference/Attributable Risk:
Incidence w/ risk factor - incidence w/o risk factor
27
Attributable Fraction:
Risk Difference/Incidence in HIGH risk group
28
Prevalence Ratio:
Prevalence w/ risk factor/ Prevalence w/o risk factor
29
Prevalence Difference:
Prevalence w/ risk factor - Prevalence w/o risk factor
30
Odds Ratio:
Odds of disease w/ risk factor/ Odds w/o risk factor
31
What answers the question "how big is the difference between the individuals with and without a particular risk factor?" for QUANTITATIVE studies?
Differences in means
32
What answers the question "how big is the difference between the individuals with and without a particular risk factor?" for QUALITATIVE studies?
Relative Risk, Prevalence Ratio, Odds Ratio, Risk Difference, Prevalence Difference, Att Fraction in the Exposed
33
Three general categories of studies:
Descriptive, Observational, Experimental
34
Two types of analytical studies:
Observational and Experimental
35
In a cohort study, you know the __________ and you are working to observe the ___________.
Exposure; Outcome
36
In a case-control study, you know the __________ and you are working to observe the ___________.
outcome; exposure
37
Three types of observational studies:
Cross-sectional Case-control Cohort
38
Cross-sectional studies identifies ______________, not _____________.
Association; Causation
39
Study that analyzes data across a population at a single point of time.
Cross-sectional
40
Characteristic of sampling for cross-sectional studies:
representative of population, not related to outcome/exposure
41
Disease measures in cross-sectional studies:
Prevalence ratio & difference Attributable fraction of the exposed Prevalence Odds Ratio
42
Limitations of cross-sectional studies:
-Least useful for establishing causal relationships -Prevalence reflects incidence & duration (can underestimate risk) -Impractical for rare diseases -Poor sampling=> unusable results
43
What type of study looks at outcomes (cases) and works backwards to find exposures?
Case-control
44
Characteristic of sampling for case-control studies:
Based on outcome of interest (cases & controls)
45
What cannot be calculated for case-control studies?
Incidence, Prevalence, Population Risk, Attributable Risk
46
What calculation can you assess with case-control studies:
Odds ratio
47
Limitations for case-control studies:
-Problems w/ temporal sequence -Values we cant calculate -Can't assess rare exposures -Appropriate control group is hard to pick -High potential for bias
48
Best study design for rare diseases:
Case-Control
49
Prospective cohort study timing:
Selects cohort at start of study and follows
50
Retrospective cohort study timing:
Comparing incidence of disease in exposed v unexposed that has already occurred
51
What is the only thing that should differ between groups in clinical trials?
Treatment
52
Types of allocation for clinical trials:
Random or Non-Random
53
Options for random allocation:
Completely random Random By Pairs Within Blocks
54
Options for non-random bias:
Systematic Historical non-random allocation Clinician's discretion
55
Specificity:
True negatives/(true negatives + false positives)
56
Sensitivity:
True Positives/(True Positives + False Negatives)
57
Positive Predictive Value:
True Positives/(True Positives+False Positives)
58
Negative Predictive Value:
True Negatives/(True Positives + False Positives)
59
Low Prevalence ____________ NPV and _____________ PPV
Increases; Decreases
60
High Prevalence ____________ NPV and _____________ PPV
decreases; increases
61
When is testing in parallel helpful:
Looking for two different markers (Ie testing for antigen in early dz and antibody in late dz)
62
Testing in series increases _________ and decreases ____________.
Specificity; Sensitivity
63
Parallel Testing increases ____________ and decreases _____________
Sensitivity; Specificity
64
EID:
Emerging infectious disease One that has appeared in a population for the first time or that may have existed previously but is rapidly increasing in incidence or geographic range
65
Three questions you should ask in an epidemiologic investigation?
Where did the disease come from? What management factors allowed it to spread? Where did it go from here?
66
Which cases should be reported?
All diagnosed/suspected cases of diseases with an APHIS control or eradication program All diagnosed/suspected cases of FADs
67
General Management of a disease outbreak:
Get diagnosis Determine and control the source stop transmission Eliminate the disease
68
Internal validity excludes the effects of:
Bias Confounding Random Error
69
Internal validity:
Does the results represent the truth in the population we are studying
70
External validity:
Can the findings be generalized to other contexts
71
The relationship between internal & external validity:
If the study lacks internal validity, then external validity is irrelevant
72
Random error vs. Systematic error:
RE is error due to chance SE error due to recognizable source Both can exist at the same time
73
Effect of bias:
Leads to the appearance of an association when there is none, or obscures an association that really exists
74
Selection Bias:
Affects WHO is in the 2x2 table
75
Information Bias:
Where in the 2x2 are people put
76
Bias towards the null:
observed value is closer to 1 (or 0 in the case of difference measurements) than is the true value
77
Bias away from the null:
observed value is farther from 1 (or 0 in the case of difference measurements) than is the true value
78
If the truth is RR=1.9 and the biased result is RR=1.4, which direction is it biased and is the association over or underestimated?
Bias towards the null True association is underestimated
79
If the truth is RR=0.4 and the biased is RR=0.7, which direction is it biased and is the association over or underestimated?
Bias towards the null True association is underestimated
80
If the truth is RR=2.0 and the biased is RR=2.6, which direction is it biased and is the association over or underestimated?
Bias towards the null True association is underestimated
81
If the truth is RR=0.5 and the biased is RR=0.3, which direction is it biased and is the association over or underestimated?
Bias towards the null True association is underestimated
82
Selection bias is most likely in what type of study?
Case-control
83
How does selection bias occur in case control studies? (2)
Control Selection Differential Participation
84
Prevention of Control Selection:
Use identical selection criteria for cases and controls
85
Prevention of differential participation:
obtain high participation rates for all groups
86
How does selection bias occur in cohort studies? (2)
Differential Participation Differential Loss to Follow-up
87
How to prevent selection bias in cohort studies?
Obtain (dif. participation) and maintain (dif. loss) high participation rates in all groups
88
Two components of misclassification bias:
How accurately can you measure exposures? How accurately can you measure disease?
89
Examples of non-differential misclassification bias:
Recall bias Interviewer Bias
90
What is the most common type of bias?
Measurement/Misclassification Error
91
Effects of non-differential measurement error:
Bias towards the null
92
Effects of differential measurement error:
Bias in either direction
93
Difference between Differential and non-differential misclassification:
Non-differential (random) has roughly equal errors between groups (masks any true difference) Differential (non-random) has better information in one group which causes over or under estimation of association
94