Epidemiology Flashcards
Epidemiology:
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
Descriptive Studies:
Describe the ocurrence and distribution of one or more variables in a population, group, or sample
Ex: Rabies by species
Analytical Studies:
Measure the relationship or association between two variables, usually a risk factor (or exposure) and an outcome
Ex: Rabies positivity rate in cats/dogs
Questions asked by descriptive studies:
Who gets sick and who doesn’t?
Where?
When?
How are cases connected?
How big is the problem?
Questions asked by analytical studies:
Why did this occur?
What can we do?
Determinants:
Host
Agent
Environments
Types of population data:
Measurement (quantitative)
Count (Categorical/Qualitative)
Examples of measurement data:
Weight, Hematocrit, BUN, Age, Survival Time, Titer, etc
Count data examples:
Breed, Sex, +/-, Old/Young, Healthy/Sick/Dead
Incidence answers what question?
What is the rate of occurrence of new cases?
Prevalence answers which question?
What proportion of animals are sick at once
Prevalence Calculation:
All Current Cases/Population at Risk
At a point in time
Incidence calculation :
NEW cases/Population at Risk
During a specific time interval
Primary Prevention:
An action that PREVENTS disease in healthy animals
Secondary prevention:
Identifying animals with disease to prevent symptoms
Tertiary Prevention:
Prevention of complications in animals who have the disease
P-Value:
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)
Significant P-Values:
<0.05
What answers the question “could the difference we found between the means be just due to chance variation?”
P-value
What answers the question “how certain are we of the size of the difference between the means?”
Confidence Interval
What answers the question “what is the rate of occurrence of new cases?”
Incidence
Case Fatality Calculation
Death among cases/total cases
What answers the question “What proportion of animals are sick at once?”
Prevalence
What answers “what proportion of cases die?”
Case Fatality Rate
Risk Ratio/Relative Risk:
Incidence w/ risk factor/incidence w/o risk factor
Risk Difference/Attributable Risk:
Incidence w/ risk factor - incidence w/o risk factor
Attributable Fraction:
Risk Difference/Incidence in HIGH risk group
Prevalence Ratio:
Prevalence w/ risk factor/ Prevalence w/o risk factor
Prevalence Difference:
Prevalence w/ risk factor - Prevalence w/o risk factor
Odds Ratio:
Odds of disease w/ risk factor/ Odds w/o risk factor
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
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
Three general categories of studies:
Descriptive, Observational, Experimental
Two types of analytical studies:
Observational and Experimental
In a cohort study, you know the __________ and you are working to observe the ___________.
Exposure; Outcome
In a case-control study, you know the __________ and you are working to observe the ___________.
outcome; exposure
Three types of observational studies:
Cross-sectional
Case-control
Cohort
Cross-sectional studies identifies ______________, not _____________.
Association; Causation
Study that analyzes data across a population at a single point of time.
Cross-sectional
Characteristic of sampling for cross-sectional studies:
representative of population, not related to outcome/exposure
Disease measures in cross-sectional studies:
Prevalence ratio & difference
Attributable fraction of the exposed
Prevalence Odds Ratio
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
What type of study looks at outcomes (cases) and works backwards to find exposures?
Case-control
Characteristic of sampling for case-control studies:
Based on outcome of interest (cases & controls)
What cannot be calculated for case-control studies?
Incidence, Prevalence, Population Risk, Attributable Risk
What calculation can you assess with case-control studies:
Odds ratio
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
Best study design for rare diseases:
Case-Control
Prospective cohort study timing:
Selects cohort at start of study and follows
Retrospective cohort study timing:
Comparing incidence of disease in exposed v unexposed that has already occurred
What is the only thing that should differ between groups in clinical trials?
Treatment
Types of allocation for clinical trials:
Random or Non-Random
Options for random allocation:
Completely random
Random
By Pairs
Within Blocks
Options for non-random bias:
Systematic
Historical non-random allocation
Clinician’s discretion
Specificity:
True negatives/(true negatives + false positives)
Sensitivity:
True Positives/(True Positives + False Negatives)
Positive Predictive Value:
True Positives/(True Positives+False Positives)
Negative Predictive Value:
True Negatives/(True Positives + False Positives)
Low Prevalence ____________ NPV and _____________ PPV
Increases; Decreases
High Prevalence ____________ NPV and _____________ PPV
decreases; increases
When is testing in parallel helpful:
Looking for two different markers (Ie testing for antigen in early dz and antibody in late dz)
Testing in series increases _________ and decreases ____________.
Specificity; Sensitivity
Parallel Testing increases ____________ and decreases _____________
Sensitivity; Specificity
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
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?
Which cases should be reported?
All diagnosed/suspected cases of diseases with an APHIS control or eradication program
All diagnosed/suspected cases of FADs
General Management of a disease outbreak:
Get diagnosis
Determine and control the source
stop transmission
Eliminate the disease
Internal validity excludes the effects of:
Bias
Confounding
Random Error
Internal validity:
Does the results represent the truth in the population we are studying
External validity:
Can the findings be generalized to other contexts
The relationship between internal & external validity:
If the study lacks internal validity, then external validity is irrelevant
Random error vs. Systematic error:
RE is error due to chance
SE error due to recognizable source
Both can exist at the same time
Effect of bias:
Leads to the appearance of an association when there is none, or obscures an association that really exists
Selection Bias:
Affects WHO is in the 2x2 table
Information Bias:
Where in the 2x2 are people put
Bias towards the null:
observed value is closer to 1 (or 0 in the case of difference measurements) than is the true value
Bias away from the null:
observed value is farther from 1 (or 0 in the case of difference measurements) than is the true value
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
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
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
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
Selection bias is most likely in what type of study?
Case-control
How does selection bias occur in case control studies? (2)
Control Selection
Differential Participation
Prevention of Control Selection:
Use identical selection criteria for cases and controls
Prevention of differential participation:
obtain high participation rates for all groups
How does selection bias occur in cohort studies? (2)
Differential Participation
Differential Loss to Follow-up
How to prevent selection bias in cohort studies?
Obtain (dif. participation) and maintain (dif. loss) high participation rates in all groups
Two components of misclassification bias:
How accurately can you measure exposures?
How accurately can you measure disease?
Examples of non-differential misclassification bias:
Recall bias
Interviewer Bias
What is the most common type of bias?
Measurement/Misclassification Error
Effects of non-differential measurement error:
Bias towards the null
Effects of differential measurement error:
Bias in either direction
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
