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1. What is the difference between incidence and prevalence? How are they calculated?
- Incidence is the number of new cases of a disease or condition in a population during a
specified period of time. Prevalence is the number of existing cases of a disease or condition in
a population at a given point in time. Incidence is calculated by dividing the number of new
cases by the population at risk during the period. Prevalence is calculated by dividing the
number of existing cases by the total population at the point in time.
- Rationale: Incidence and prevalence are two important measures of disease frequency that
help to describe the distribution and determinants of health and disease in populations.
2. What are the three types of epidemiological studies? Give an example of each type and
explain its advantages and disadvantages.
- The three types of epidemiological studies are descriptive, analytical, and experimental.
Descriptive studies describe the distribution of a disease or condition by person, place, and
time. They are useful for generating hypotheses and identifying patterns. An example of a
descriptive study is a case report or a cross-sectional survey. Analytical studies test hypotheses
about the associations between exposures and outcomes. They are useful for identifying risk
factors and causal relationships. An example of an analytical study is a cohort study or a case-
control study. Experimental studies manipulate exposures and compare outcomes between
groups. They are useful for testing interventions and evaluating their effectiveness. An example
of an experimental study is a randomized controlled trial or a community trial.
- Rationale: The three types of epidemiological studies have different designs, purposes, and
strengths and limitations that affect their validity and applicability.
3. What are the criteria for establishing causality between an exposure and an outcome? Name
and explain each criterion.
- The criteria for establishing causality between an exposure and an outcome are consistency,
strength, specificity, temporality, biological gradient, plausibility, coherence, experiment, and
analogy. Consistency means that the association is observed repeatedly in different populations
and settings. Strength means that the association is strong and not likely to be due to chance or
confounding. Specificity means that the exposure is associated with only one outcome and vice
versa. Temporality means that the exposure precedes the outcome in time. Biological gradient
means that there is a dose-response relationship between the exposure and the outcome.
Plausibility means that there is a biological or logical explanation for the association. Coherence
means that the association is compatible with existing knowledge and evidence. Experiment
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