Epidemiology Flashcards
1
Q
What is the definition of prevalence?
A
measure of the total number of people in a specific group who have (or had) a certain disease, condition, or risk factor (such as smoking or obesity) at a specific point in time or during a given period of time.
2
Q
In a Cohort study, do you use risk ratio or odds ratio?
A
Risk Ratios (Entire population at risk is in the study}.
3
Q
In a Case Control study, do you use a risk ratio or odds ratio?
A
Odds Ratio (Entire population at risk is not in the study)
4
Q
What is the equation for the odds ratio?
A
ad/bc
5
Q
What is the risk ratio?
A
Risk Among the Exposed/Risk Among the Unexposed
6
Q
What is the equation for the risk exposed?
A
a/a+b
7
Q
What is the equation for the risk unexposed?
A
c/c+d
8
Q
What is point prevalence?
A
Subjects with at disease at a point in time/Population at the same time
9
Q
What is period prevalence?
A
Subjects with a disease for a given time interval/Population at mid-interval
A+C/A+B+C+D
Attack Rate = Period Prevalence during epidemic
10
Q
When do you use case control studies?
A
They seek to identify possible predictors of outcome and are useful for studying rare diseases or outcomes. They are often used to generate hypotheses that can then be studied via prospective cohort or other studies.
11
Q
How should you select controls?
A
Should be representative of the population from which one got the cases at the same level of exposure.
12
Q
What are the three main types of observational study designs?
A
- cohort studies
- case–control studies
- cross-sectional studies
13
Q
What is a 2X2 Table for Disease and Disease Testing
A
14
Q
What is the 2X2 Table to Determine the Truth in the Population
A
15
Q
Using a 2X2 Table to Determine the Type 1 Error Rate
A
16
Q
Using a 2X2 Table to Determine the Type 2 Error Rate
A
17
Q
Using a 2X2 Table to Determine the Power of a Test
A
18
Q
True or False: Prevalence is a measure of Morbidity.
A
True (Prevalence is water in a bucket)
19
Q
How do you determine the probability or risk in a case control study?
A
Number of times something occurs/# possible occurrences
OR
Odds/(1+Odds)
20
Q
How do you determine the Odds in a case control study?
A
Number of times something occurs/# of times it does not
OR
Probability/(1-probability)
21
Q
How do you calculate the Odds Ratio in a Case Control Study and how do you interpret it?
A
OR = ad/bc
1 = Same
>1 = Greater among cases
<1 = Less among cases
22
Q
What is the Ecologic Fallacy?
A
Formal fallacy in the interpretation of statistical data that occurs when inferences about individual are gleaned from the group to which they belong.
23
Q
Name 5 Ways to Avoid Confounding/Bias
A
1) Stratification
2) Randomization (not possible in observational studies)
3) Restriction (one group)
4) Matching (similar groups)
5) Multivariate Analysis
24
Q
What is a cohort study?
A
Defined population at risk AND when possible to get data from all members or a representative sample of the cohort.
25
How do you measure prevalence in a cohort study?
Number of ILL subjects/Total population at risk during at a particular point in time
26
What is the risk or attack rate?
Number of ILL people/number of people at risk
Exposed+ILL/Exposed
27
How does one measure the risk ratio in a cohort study and how do you interpret it?
Risk Exposed/Risk of Non-exposed
RR = 1 no association
RR = >1 exposure positively related
RR = <1 exposure negatively related
28
What is confounding?
A variable that influences both the dependent variable and independent variable, causing a spurious association.
Associated with the outcome (is a risk factor for the disease)
AND Associated with the exposure, but is not a result of the exposure (is not on the causal pathway from exposure to outcome).
29
What is effect modification?
The association between the exposure and the disease is different for different levels of a third variable. In other words, the effect of the exposure on the disease is modified by the third variable. Effect modification is a finding to be reported, not a bias to be eliminated; it is a “natural phenomenon” that exists independently of the study design.
30
In a stratified analysis how do you know if you have confounding or effect modification?
EM = Stratum specific measures are different from one another and the crude falls between them (REPORT SS)
Confounding = stratum specific measures are similar and at least 10% different from the crude and it does not fall between them. (REPORT ADJUSTED MEASURE)
IF NOTHING IS A COVARIABLE = REPORT CRUDE
31
What is the relative risk when it comes to vaccine epidemiology (Exposed means unvaccinated)?
Risk Exposed/Risk Unexposed
32
What is the attributable risk or risk difference when it comes to vaccine epidemiology (Exposed means unvaccinated)?
Risk Exposed - Risk Unexposed X 100
33
What is the attributable fraction in vaccine epidemiology?
RR-1/RR
34
How do you calculated vaccine efficacy?
RU - RV/RU X 100
35
Please review the following example of vaccine efficacy 2X2 table and equations.
36
Name the quality of data sources in descending order.
1. Meta Analysis
2. Randomized clinical trial
3. Cohort study
4. Case Control Study
5. Cross- Sectional Analysis
6. Case Reports or Studies
7. Mechanistic Studies
8. Editorials or expert opinions
37
What is the Basic Reproductive Number (R0)
Average number of secondary cases produced by each case in a totally susceptible population. How fast a disease occurs in a population.
R0 = CXPXD
D = duration of infectiousness of the case
C = number of contacts made per unit of time
P = probability of transmission/contact event
38
What is the net reproduction number (R)?
The average number of secondary cases per case in a population where not all of the individuals are susceptible.
39
What does the value of the R0 mean/determine?
>1 = an epidemic will occur
<1 = an epidemic will not occur
>3 = almost all hosts will be infected
40
What is the equation to determine the level of vaccination coverage to end an outbreak or prevent one (level of herd immunity)?
Herd Immunity = {1-1/R0}
41
How do you calculate the Herd Immunity Threshold?
HIT = R0-1/R0
42
What is the herd immunity threshold?
Proportion of the population that has to be immune in order for a disease to be static. If the immune number exceeds this level, the net R0 is less than 1, the disease will die out.
43
Review this example of a HIT calculation.
R0 for measles in a completely susceptible population is 11.
HIT = (11-1)/11 = 91% (must be immune for disease to stabilize)
44
What is the latent period?
Time from infection until the individual can transmit the infection
45
What is the infectious period?
Time that the individual can transmit the infection
46
What is the incubation period?
Time from infection to the development of symptoms.
47
What is vaccine efficacy?
Percent reduction in the disease in optimal settings
VE = 1- relative risk of getting disease among the vaccinated
48
What is vaccine effectiveness?
Ability to prevent disease in the real world (host factors, mode of delivery)
49
What is vaccine coverage?
Percent of the population vaccinated (access, education, hesitancy)
50
What is the prevented fraction in vaccinology?
51
What are the categorical measures of occurrence?
Frequencies = Percentages/Proportions
- Incidence = New cases in a specified time/population
- Prevalence = All cases/population
- Odds = Cases/non-cases
52
What are the continuous measures of occurence?
- Means = average
- Median = middle
- Standard Deviation/Error = The average extent to which occurrences deviate from the mean
53
What are the measures of effect?
Relative Risk
- Risk/Rate Ratio
Incidence in exposed/unexposed
- Odds Ratio
Cohort: Odds of outcome in exposed/odds of outcome in
unexposed
Case Control: Odds of exposure in cases/odd of exposure
in controls
- Risk Difference (attributable risk)
Incidence in one population - another population
54
What is a confidence interval?
Level of certainty that the true mean/proportion lies within the calculated sample interval
55
In the tests for significance what is hypothesis testing?
P Value: probability of obtaining the observed (or more extreme) result if the null hypothesis is true
- Chi squared
- Z test, T test, Pearson's, Spearman's
56
Review the table of significance testing in different situations?
57
Bias-Confounding
58
What is the equation for attributable risk?
[a/(a+b)] - [c/(c+d)]/[a/(a+b)]
59
What is probability sampling?
Every subject in the study population has a known and equal chance of getting selected (Best chance to get a truly representative population)
60
When do you use random sampling and what are its advantages?
Decrease sampling bias and cost effective
61
When do you use stratified sampling and what are its advantages?
Usually diverse population and simple
62
When do you use random cluster sampling and what are its advantages?
Accurate sample and non-technical
63
Define the null hypothesis in linear regression.
Null hypothesis in linear regression (H0) = no association between predictor and outcome (OR or RR = 1)
64
What do P values represent for each predictor in linear regression?
The probability that the test stat would be as large or larger than the calculated if the null were true (small P value < 0.05, reject the null)
65
Does failing to reject the null mean that it is true?
No. Type II error or the sample was not large enough
66
What are the measures of central location?
Mean = Average
Median = (n+1)/2
Mode = Value that occurs the most often
67
What are the measures of risk?
Rate: frequency of an event in defined population
Ratio: relative magnitude of 2 quantities or a comparison of any 2 values
Proportion: # of events with a particular characteristic/total # of events in which the numerator is a subset.
68
What is the Standard Deviation and how do you calculate it?
Measure of Spread
1. Calculate the arithmetic mean
2. Subtract the mean from each observation
3. Square the differences
4. Sum the squared differences
5. Divide that number by n-1
6. Take the square root of step 5
69
What is the Z score?
(Data point - Pop Mean)/pop standard deviation
Z score = Tells the number of standard deviations from the mean
70
Define Bias?
Systematic error in the design, conduct or analysis of a study that results in a mistaken estimate of the exposures effect on the risk of disease.
71
What are the types of bias?
1. Selection Bias
2. Information Bias
3. Confounding
72
What is variance and how do you calculate it?
Variability among data points (more detailed than the spread)
73
What are the seven levels in the hierarchy of evidence?
1. Systematic review or meta-analysis of all RCTs or evidence based on clinical practice guidelines
2. Well-Designed RCT
3. Well-Designed Controlled Trial without Randomization
4. Case control, cohort or cross-sectional study
5. Systematic review of descriptive or qualitative studies
6. Quantitative Description or Qualitative Studies
7. Expert opinion, reports, textbooks or non-EBP guidelines
74
What type of data is an ANOVA used to analyze?
Continuous data with similar variances
75
What test do you use to determine if there are similar variances?
Bartlett's Test
P value of > 0.05 use ANOVA
P value of < 0.05 do not use ANOVA
76
When is a t-test used?
A t-test is used when the sample size is less than 30 and the population variance is unknown (compare 2 groups)
77
When is an F-Test used?
Utilized to determine whether two populations' variances are equal
78
If you can't use an ANOVA, what do you use?
Kruskal Wallis Test or one-way ANOVA on ranks is a non-parametric method for testing whether samples originate from the same distribution. Used for comparing two or more independent samples of equal or different sample sizes. It extends the Mann–Whitney U test, which is used for comparing only two groups. The parametric equivalent of the Kruskal–Wallis test is the one-way analysis of variance (ANOVA).
79
What is the relationship to the source population in Cohort studies as compared to Case Controls?
Cohort is the entire cohort or representative sample and Case-Control is some sick and some not
80
Who are the subjects in Cohort studies as compared to Case Controls?
Exposure VS. Disease
81
Which costs more, case control or cohort study?
Cohort
82
What is the main advantage and disadvantage of a Cohort study?
Can estimate risk and can be time and labor intensive
83
What is the main advantage and disadvantage of a Case-Control study?
Do not have to find or use the entire cohort
Cannot estimate risk in a population
84
What type of study is a cross-sectional study?
Prevalence study
- Measures the prevalence of outcomes or determinants of health or both in a population at a point in time
85
What are the strengths of a cross-sectional study?
May be first step in assessing association and it's efficient
86
What are the limitations of a cross-sectional study?
Cannot determine temporal relationship (no conclusions about causality)
Prevalent rather than indirect cases, data reflect determinants of survival and etiology
87
What does a 2X2 table for a cross sectional study look like?
88
What are the 9 criteria for a causal relationship?
1. Temporal relationship (most important)
2. Strength of association
3. Biologic Plausibility*
4. Dose-Response Relationship
5. Replication of Findings*
6. Effect of removing the exposure
7. Extent to which alternative explanations have been considered (adjustment for confounding)*
8. Specificity of the association
9. Consistency with other knowledge
89
What is a confidence interval?
Reports the level of certainty in calculated point estimates (OR and RR) (Measure of Association) Brings precision
Indicates the expected range of values a variable may have (Wide Range = Less Certain, Narrow- More Certain)
90
What does a 95% Confidence Interval Mean?
If we repeated the study an infinite number of times and created a CI for each; 95% would contain the true parameter
95% Z = 1.96
90% Z = 1.64
Lower = Mean - 1.96 X SD
Upper = Mean + 1.96 X SD
91
If the 95% CI includes the null value (OR or RR =1) what does that mean?
Not statistically significant
92
What is linear regression?
Outcome variable is measured on a continuous scale and relationship between outcome and predictor is a straight line
93
What is logistic regression?
Outcome variable only has 2 possible outcomes (dichotomous), most commonly presence or absence of disease (univariable is 1 predictor and multi is > 1)
94
What are the regression method variables?
Response Variable = dependent variable or outcome variable (disease)
Predicator Variable = independent variable or explanatory or exposure variable (XIV) x axis is independent variable
95
Predictor variables can be what types?
Continuous (numeric) or
Categorical (often binary)
Maybe ordinal or nominal (no order) or dichotomous or binary (only 2 categories)
96
When is a T-test used?
When the population standard deviation is not known
Parametric test for the difference between means of independent samples (continuous data)
H0 = mean1 = mean 2
HA = mean 1 not equal to mean2
97
What is the equation for the T-Test?
T = Sample mean- population mean/sample SEM
Calculated value is comparted to value in the t-table and if the t -value is = or > the table = significant
98
How is the Chi Squared Test Used (Categorical Data)?
Test whether the observed differences in the proportions between the study groups are significant (i.e. is there an association between exposure and outcome?). Observations must be independent.
99
What is the equation for the Chi Squared Test?
Must be 30 observations
O = Observed count in category
E = Expected count un the category under null
H0 = proportions are equal
HA = proportions are different
100
Explain the Chi Square 2 X 2 Table.
101
How do you calculate the matched odds ratio
OR Matched = B/C
Calculate the Crude OR = (A+B) X (B+D)/(C+D) X (A+C)
102
What is the standard error of the mean and how is it related to confidence intervals?
SEM = standard deviation of the sample/square root of the number in the sample
CI = Sample mean +/- 2 SEM
Mean +/- one SEM is a CI of 68.5 percent
Mean +/- two SEM is a CI of 95%
Mean +/- three SEM is a CI of 99%
103
What do logistic regression coefficients show?
Association not Causation
104
What is logistic regression?
Logistic regression is a statistical analysis method to predict a binary outcome, such as yes or no, based on prior observations of a data set. A logistic regression model predicts a dependent data variable by analyzing the relationship between one or more existing independent variables.
105
What is the equation for logistic regression?
E = error term (accounts for variability)
B0 = Intercept (log odds of the probability of disease if all predictor variables are absent
B1 = Coefficients
- If dichotomous - represents the log odds of disease change when factor is present
- If continuous - represents the log odds of disease change with unit increase of the predictor
106
What is parallel testing?
Two tests at the same time and only one needs to be positive (Rules Out Disease)
- Patient needs to prove that it is healthy
- Increases sensitivity and NPV
- Fewest false negatives possible even if a few false positives
- Consequences of not identifying a positive animal are catastrophic
107
What is serial testing?
Two or more tests run and all must be positive to conclude positive (Rules in Disease)
- Patient must prove that they are affected
- Increases specificity and PPV
108
What are likelihood ratios?
Likelihood ratios (LR) are used to assess two things: 1) the potential utility of a particular diagnostic test, and 2) how likely it is that a patient has a disease or condition. LRs are basically a ratio of the probability that a test result is correct to the probability that the test result is incorrect. The sensitivity and specificity of the test are the numbers used to generate a LR, which is calculated for both positive and negative test results and is expressed as ‘LR+’ and ‘LR-‘, respectively. The calculations are based on the following formulas:
LR+ = sensitivity / 1- specificity
LR- = 1- sensitivity / specificity
109
How does prevalence effect PPV and NPV?
PPV increases when prevalence increases
NPV slightly decreases when prevalence increases
110
What is the difference between incubation and latency as applied to infectious disease?
Chronicity (latency more chronic)
111
What is the definition of infectivity?
Proportion of exposed subjects who become infected
112
What is the definition of pathogenicity?
Proportion of infected subjects who develop disease
113
What is the definition of virulence?
Refers to the proportion of clinically apparent cases that are severe or fatal
114
What are the steps in an outbreak investigation?
1. Prepare for field work
2. Establish the existence of an outbreak
3. Verify the diagnosis
4. Define and identify cases
5. Describe and orient the data in terms of time,
place, and subject
6. Develop hypotheses
7. Evaluate hypotheses
8. Refine hypotheses and carry out additional studies
9. Implement control and prevention measures
10. Communicate findings
115
What is an epidemic curve?
An epi curve provides key information about an outbreak, including how quickly it is growing, what type of food may be causing it, and whether it is ongoing.
- Time trend of the outbreak, that is, the distribution of cases over time.
- “Outliers,” or cases that stand apart from the overall pattern.
- General sense of the outbreak's magnitude.
- Inferences about the outbreak's pattern of spread.
- Most likely time of exposure.
116
Explain differential vs. non differential misclassification
Non-differential misclassification occurs when the probability of individuals being misclassified is equal across all groups in the study. Differential misclassification occurs when the probability of being misclassified differs between groups in a study (bias is either toward or away from the null)
If outcome is dichotomous then NDM causes a bias toward the null (risk ratio, rate ratio or odds ratio)
117
What is the main difference between and 1 and 2 tailed test?
The main difference between one-tailed and two-tailed tests is that one-tailed tests will only have one critical region whereas two-tailed tests will have two critical regions.
(Hypothesis in which the alternative has 1 or 2 ends) What is the difference between one-tailed and two-tailed test in Excel?
For example, a one-tailed test might determine only whether Method B is greater than Method A. Two-tailed tests can detect differences in either direction—greater than or less than.
118
Confounding Table Example
119
What study plan would be best to determine the effectiveness of a new vaccine in preventing disease in humans?
Cohort Study
120
An investigator is performing a study to examine the effect of being overweight on experiencing CCL tears in dogs. The investigator also wants to control for age and spay/neuter status. What statistical technique does the investigator need to use to test her hypothesis?
Logistic regression – since the outcome is categorical (injury or no injury) and multiple predictors are being examined, logistic regression is needed. Chi-square test could be used if we were only looking at effect of being overweight on CCL tears, but since we want to adjust for other factors, we need a multivariable model.
121
In this test, a stool sample is tested for the presence of blood. If the Hemoccult test result is negative, no further testing is done. If the Hemoccult test result is positive, the individual will have a second stool sample tested with the Hemoccult II test. If this second sample also tests positive for blood, the individual will be referred for more extensive evaluation. What is this type of screening called, and what is the effect on net sensitivity and net specificity of this method of screening?
This is serial testing, which reduces sensitivity but increases specificity. This is because, in series testing, it is harder to be a “true” negative (you need to have two tests be positive to say you have the disease), but it is easier to be a “true” negative (only need one negative result to be called disease-free)
122
How does non-differential misclassification bias affect the odds ratio or relative risk
Non-differential misclassification of a dichotomous outcome will generally bias toward the null (i.e., closer to a RR or OR of 1, or no effect). This is usually because it dilutes the true effect.
123
How does differential misclassification bias affect the odds ratio or relative risk?
Differential misclassification can move the numerical value of the OR or RR closer to one or further away from one. That is, it can underestimate or overestimate the strength of association (you rarely know which until it happens).
124
What type of chi square test do you use when?
125
Decision Tree for the analysis of continuous data
126
What does parallel testing do to the sensitivity/specificity and Predictive Values?
Increased Sensitivity and Negative Predictive Value
Decreased Specificity and Positive Predictive Value
Patient has to prove that it is healthy!
127
What does serial testing do to the sensitivity/specificity and Predictive Values?
Increases Specificity and Positive Predictive Value
Decreases Sensitivity and Negative Predictive Value
Patient has to prove that it has disease!
128
9. An epidemic curve displays:
a. The population at risk versus the frequency of cases.
b. The frequency of cases versus the number of ill in the population.
c. The time of onset versus the population at risk.
d. The time of onset versus the frequency of incident cases.
e. The time of onset versus the number of individuals who are ill.
d. The time of onset versus the frequency of incident cases
129
What study plan would be best to determine the effectiveness of a new vaccine in preventing disease in humans?
a. Case-control study.
b. Cohort study.
c. Prevalence study.
d. Morbidity study.
e. Retrospective study.
b. Cohort study.
130
Which of the following agent characteristics is most likely to be seen in a disease which occurs in epidemic proportions:
a. High infectivity
b. High pathogenicity
c. High virulence
d. Low antigenicity
e. Viability
a. High infectivity
131
In a study of alcohol and oral cancer the relative risk is 2.0 for men and 2.0 for women but 4.0 for both sexes combined. This suggests that:
a. There is confounding by sex in these data
b. There is confounding by some unknown or unmeasured factor in these data
c. There is evidence of effect modification in these data
d. The results have been adjusted for age and sex
e. The results are due to bias
a. There is confounding by sex in these data
132
Epidemiologic models can be useful for all of the following except:
a. Predicting effectiveness of programs
b. Organizing and storing knowledge about a disease process
c. Predicting risk or consequences of disease
d. Identifying an individual’s risk factors for disease
e. Developing policy
d. Identifying an individual’s risk factors for disease
133
To be effective, surveillance systems should incorporate all of the following except:
a. Generation of information for action
b. Disease eradication
c. Ongoing data collection
d. Systematic data collection
e. Timely information dissemination
b. Disease eradication
134
In a study of alcohol and oral cancer the relative risk is 2.0 for men and 2.0 for women but 4.0 for both sexes combined. This suggests that:
a. There is confounding by sex in these data
b. There is confounding by some unknown or unmeasured factor in these data
c. There is evidence of effect modification in these data
d. The results have been adjusted for age and sex
a. There is confounding by sex in these data
135
In a country where a disease is endemic:
a) The number of affected animals tends to stay more or less constant over time
b) There have been at least 2 outbreaks of that disease in the past 5 years
c) The disease has persisted in that population for a long time
d) The vaccine for that disease is probably not used in a widespread manner
c) The disease has persisted in that population for a long time
136
A randomized trial comparing the efficacy of two drugs showed a difference between the two (with a P value < 0.05). Assume that in reality, however, the two drugs do not differ. This is therefore an example of:
a. Type I error (alpha error)
b. Type 2 error(beta error)
c. 1- alpha
d. 1- beta
e. None of the above
a. Type I error (alpha error)
137
In cohort studies of the role of a suspected factor in the etiology of a disease, it is essential that (select all that apply):
a. There be equal numbers of persons in both study groups
b. At the beginning of the study, those with the disease and those without the disease have equal risks of having the factor
c. The study group with the factor and the study group without the factor be representative of the general population
d. The exposed and nonexposed groups under study be as similar as possible with regard to possible confounding factors
d. The exposed and nonexposed groups under study be as similar as possible with regard to possible confounding factors
