Epidemiology is the scientific study of the distribution and determinants of health-related events in populations. Statistical methods form the backbone of epidemiological research, allowing researchers to measure disease frequency, analyze associations, and make evidence-based decisions. Understanding these methods helps Pharm.D students interpret public health data and evaluate clinical risks effectively.
1. Measures of Disease Frequency
Incidence
Incidence measures the number of new cases of a disease occurring in a population during a specific period. It helps determine the risk of developing a disease.
Incidence Rate = (New Cases / Population at Risk) × 1000
Prevalence
Prevalence measures the total number of existing cases (new + old) at a particular time. It reflects the burden of a disease in a community.
Prevalence = (Existing Cases / Total Population) × 100
2. Measures of Association
Relative Risk (RR)
Relative Risk compares the risk of disease in the exposed group to the unexposed group. It is commonly used in cohort studies.
RR = [Incidence in Exposed] / [Incidence in Unexposed]
RR > 1 indicates increased risk; RR < 1 suggests protective effect.
Odds Ratio (OR)
Odds Ratio measures the odds of exposure among cases compared to controls. It is the primary measure used in case-control studies.
OR = (a × d) / (b × c)
Attributable Risk (AR)
AR indicates how much of the disease risk is directly due to exposure. It helps assess the public health impact of removing a harmful exposure.
AR = Incidence in Exposed − Incidence in Unexposed
3. Study Designs and Statistical Methods
Cohort Studies
- Measure incidence.
- Use Relative Risk (RR) for associations.
- Suitable for studying multiple outcomes.
Case-Control Studies
- Measure exposure differences between cases and controls.
- Use Odds Ratio (OR) as the primary measure.
- Useful for rare diseases.
Cross-Sectional Studies
- Measure prevalence.
- Useful for assessing disease burden in a population.
Randomized Controlled Trials (RCTs)
- Use hypothesis testing to evaluate treatment effects.
- Estimate risk differences and number needed to treat (NNT).
4. Hypothesis Testing in Epidemiology
- Chi-square test: Used for comparing proportions.
- t-test / ANOVA: Used for comparing means across groups.
- Regression analysis: Used for modeling risk factors.
- Confidence intervals: Evaluate precision of estimates.
5. Screening Test Evaluation
Sensitivity
Ability of a test to correctly identify individuals with the disease.
Sensitivity = True Positives / (True Positives + False Negatives)
Specificity
Ability of a test to correctly identify individuals without the disease.
Specificity = True Negatives / (True Negatives + False Positives)
Positive Predictive Value (PPV)
Probability that an individual with a positive test truly has the disease.
Negative Predictive Value (NPV)
Probability that an individual with a negative test truly does not have the disease.
6. Epidemic and Outbreak Analysis
- Epidemic curves: Visual representation of case distribution.
- Basic reproductive number (R₀): Measures infectiousness.
- Attack rate: Used in outbreak investigations.
Applications of Statistical Methods in Epidemiology
- Detecting disease outbreaks.
- Evaluating drug safety and adverse effects.
- Planning and monitoring public health programs.
- Identifying risk factors and protective factors.
- Assessing impact of preventive measures.
Detailed Notes:
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