Basic concepts

Question 1

Relationship between prevalence and incidence rate

Answer 1

Prevalence is proporational to the incidence mutiplied by the average duration of the disease.

Question 2

Objectives of epidemiology

Answer 2

1. Investigation, monitoring and surveillance of disease of known and unknown origin.
2. Understand the ecology and natural history of disease (i.e. risk factors)
3. Evalute tests, treatments, disease control programs in terms of performance and economic benefits.

Question 3

Temporal patterns of disease within a region and between regions

Answer 3

Sporadic (no pattern), endemic (constant low level, predictable), epidemic (beyond expected level, not predictable), pandemic (an epidemic that crosses international borders).

Question 4

Risk and open populations

Answer 4

Cannot calculate risk for an open population, but it can be estimated from the incidence rate.

Question 5

Three types of bias in screening

Answer 5

1. Lead time (longer survival due to early diagnosis)
2. Length time (longer survival due to milder disease)
3. Self selection (longer survival due to volunteer bias - usually lower risk individuals)

Question 6

True prevalence vs apparent prevalence

Answer 6

True prevalence = actual level of disease in the population.

Apparent prevalence = level of disease in the population according to the test results

Question 7

To confirm or rule-in a disease

Answer 7

Need a test with high specificity, to minimize the false positives. (To make sure those to test positive are truly positive)

Question 8

To confirm the absence of disease or rule out a disease

Answer 8

Need a test with high sensitivity to minimize the false negatives. (To make sure that those who test negative are truly negative).

Question 9

What happens when the cutpoint of a continuous or ordinal scale test is increased?

Answer 9

The specificity and false negatives increase, the sensitivity and false positive decrease

Question 10

What happens when the cutpoint of a continuous or ordinal scale test is decreased?

Answer 10

The sensitivity and false positives increase, the specificity and false negatives decrease

Question 11

Two main types of error

Answer 11

1. Random error

2. Systematic error

Question 12

Three main types of bias

Answer 12

1. Information bias
2. Selection bias
3. Confounding

Question 13

Causes of information (misclassification) bias

Answer 13

1. Recall bias
2. Observer bias (interviewer bias)
3. Inaccurate diagnostic tests or poor questionnaire
4. Non-compliance with treatment in RCT
5. Using ecological level data at individual level classification

Question 14

Direction of non-differential misclassification (information) bias

Answer 14

Always biases towards the null

Question 15

Direction of differential misclassification (information) bias

Answer 15

Bias may occur in either direction (towards or away from the null)

Question 16

Examples of selection bias

Answer 16

1. Non-response bias
2. Admission risk/Berkson’s bias
3. Poor choice of comparison group
4. Loss to follow up (also Hawthorne effect)
5. Selective entry/survival bias
6. Detection/Surveillance bias

Question 17

How to avoid selection bias:

Choice of comparison groups

Answer 17

Good study design - select from the same source, random sampling

Question 18

How to avoid selection bias:

Non-response bias

Answer 18

Gather information on non-responders, compare non-responders to responders

Question 19

How to avoid selection bias:

Admission risk/Berkson’s bias

Answer 19

Consider factors that may lead to or exclude individuals from the secondary base
Include only conditions that are not associated with the exposure of interest

Question 20

How to avoid selection bias:

Loss to follow up

Answer 20

Good study design and implementation.
Collect good contact information for study subjects.
Follow all groups completely/with equal rigor.

Question 21

How to avoid selection bias:

Selective entry/survival bias

Answer 21

Select from animals/people that were ever in the group, not just those that are currently in the group.

Question 22

How to avoid selection bias:

Detection/Surveillance bias

Answer 22

Use the same diagnostic technique for all participants.

Question 23

To qualify as a confounder, a variable must:

Answer 23

1. Be associated with the outcome
2. Be associated with exposure
3. Not be a consequence of exposure (not an intervening or intermediate variable)

Question 24

Three types of epidemiologic studies

Answer 24

Observational (descriptive, analytical), controlled experiments (RCT), theoretical studies (math models, simulations)

Question 25

Inputs needed to calculate sample size in descriptive studies

Answer 25

1. Continuous outcome (means) = a priori estimate of population variance, desired precision of the estimate and confidence level
2. Dichotomous outcome (proportions) = expected prevalence, desired precision of the estimate and confidence level

Question 26

Inputs needed to calculate sample size in analytic studies

Answer 26

1. Continuous outcome (means) = a priori estimate of the means in two groups (effect size), expected variance in the data, desired confidence level and power
2. Dichotomous outcome (proportions) = a priori estimates of the proportions in two groups, desired confidence level and power

Question 27

Inputs needed to adjust for clustering in descriptive studies

Answer 27

Initial sample size, average size of each group, intraclass correlation coefficient

Question 28

Inputs needed to adjust for a finite population in descriptive studies

Answer 28

Initial sample size, total population size

always round up

Question 29

Inputs needed to calculate sample size to detect disease or determine freedom from infection (finite population)

Answer 29

Minimum expected prevalence, desired confidence level, size of the population (assumes a perfect test)

Question 30

Inputs needed to calculate sample size to detect disease or determine freedom from disease (infinite population)

Answer 30

Minimum expected prevalence, desired confidence level (assumes a perfect test, calculates approximate sample size)