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Epidemiology

The study of the distribution and determinants of health-related states in populations, and the application of this study to control health problems.

Study Designs

Study Designs is a clinical topic covering pathophysiology, diagnosis, evidence-based treatment, and patient care.

Key points: Design principles, analysis methods, standards and codes, and real-world case studies.

Measures of Association

Measures of Association is a clinical topic covering pathophysiology, diagnosis, evidence-based treatment, and patient care.

Key points: Core principles, practical applications, and advanced concepts that build deep understanding.

Confounding & Bias

Confounding & Bias is a clinical topic covering pathophysiology, diagnosis, evidence-based treatment, and patient care.

Key points: Core principles, practical applications, and advanced concepts that build deep understanding.

Outbreak Investigation

Outbreak Investigation is a clinical topic covering pathophysiology, diagnosis, evidence-based treatment, and patient care.

Key points: Core frameworks, analytical tools, and real-world case studies with quantitative examples.

Screening & Surveillance

Screening & Surveillance is a clinical topic covering pathophysiology, diagnosis, evidence-based treatment, and patient care.

Key points: Core principles, practical applications, and advanced concepts that build deep understanding.

Measures of Disease Frequency

Measures of Disease Frequency is a clinical topic covering pathophysiology, diagnosis, evidence-based treatment, and patient care.

Key points: Structure and function, clinical presentation, diagnostic criteria, and evidence-based management.

Causal Inference

Causal Inference is a clinical topic covering pathophysiology, diagnosis, evidence-based treatment, and patient care.

Key points: Core principles, practical applications, and advanced concepts that build deep understanding.

Epidemiologic Transition

Epidemiologic Transition is a clinical topic covering pathophysiology, diagnosis, evidence-based treatment, and patient care.

Key points: Core principles, practical applications, and advanced concepts that build deep understanding.

Key Formulas & Equations

Incidence Rate: IR = (New cases during period / Population at risk) ร— K
Incidence Density: ID = New cases / Person-time at risk
Point Prevalence: P = (Existing cases at point / Population) ร— K
Period Prevalence: PP = (Cases during period / Population) ร— K
Relative Risk: RR = [a/(a+b)] / [c/(c+d)] = Ie/Iu
Odds Ratio: OR = ad/bc
Attributable Risk: AR = Ie - Iu
Attributable Fraction: AF = (Ie - Iu)/Ie ร— 100%
Sensitivity: Sn = TP/(TP+FN)
Specificity: Sp = TN/(TN+FP)
PPV: PPV = TP/(TP+FP)
NPV: NPV = TN/(TN+FN)
Mortality Rate: MR = (Deaths / Mid-year population) ร— K
Age-Specific Mortality: ASMR = (Deaths in age group / Population in age group) ร— K
Standardized Mortality Ratio: SMR = Observed / Expected
PYLL: Potential Years of Life Lost = ฮฃ(age at death - endpoint)
Vaccine Efficacy: VE = (ARU - ARV)/ARU ร— 100%
Herd Immunity Threshold: HIT = 1 - 1/Rโ‚€
Basic Reproduction Number: Rโ‚€ = ฮฒ ร— D ร— N
Force of Infection: ฮป = (Number of new cases / Susceptible population) ร— K

Core Concepts

Study Designs

Types of epidemiologic studies: cohort (follow exposed/unexposed), case-control (compare cases/non-cases), cross-sectional (snapshot), and experimental (RCTs).

Measures of Association

Quantifying exposure-disease relationships: relative risk, odds ratio, attributable risk, and population attributable risk.

Confounding & Bias

Distortion of exposure-disease relationships. Confounding by third variables; bias from selection, information, or measurement error.

Outbreak Investigation

Systematic approach to investigate disease outbreaks: verify diagnosis, define cases, descriptive epidemiology, hypothesis testing, and control measures.

Screening & Surveillance

Screening: early detection of disease in asymptomatic individuals. Surveillance: ongoing systematic collection and analysis of health data.

Measures of Disease Frequency

Incidence (new cases), prevalence (total cases), and their uses in different study designs and public health planning.

Causal Inference

Bradford Hill criteria: strength, consistency, specificity, temporality, biological gradient, plausibility, coherence, experiment, analogy.

Epidemiologic Transition

Shift from infectious to chronic diseases as societies develop. Explains changing disease patterns over time and across populations.

Worked Examples

Example 1: Relative Risk

Problem: Cohort study: 100 exposed, 20 developed disease; 200 unexposed, 10 developed disease. Calculate RR.

Solution:

Ie = 20/100 = 0.20; Iu = 10/200 = 0.05

RR = 0.20/0.05 = 4.0 (exposed have 4ร— risk)

Example 2: Screening Test

Problem: Test results: TP = 90, FN = 10, FP = 20, TN = 880. Calculate sensitivity and specificity.

Solution:

Sensitivity = 90/(90+10) = 90%

Specificity = 880/(880+20) = 97.8%

Example 3: Odds Ratio

Problem: Case-control: cases with exposure = 60, cases without = 40; controls with exposure = 30, controls without = 70. Calculate OR.

Solution:

OR = (60 ร— 70)/(40 ร— 30) = 4200/1200 = 3.5

Practice Problems

Problem 1

Calculate incidence rate if 150 new cases occur in 10,000 population at risk. Express per 1,000.

Answer: IR = 150/10,000 ร— 1,000 = 15 per 1,000 per year

Problem 2

Calculate PPV if TP = 80, FP = 40.

Answer: PPV = 80/(80+40) = 66.7%

Problem 3

Calculate attributable risk if Ie = 0.15 and Iu = 0.05.

Answer: AR = 0.15 - 0.05 = 0.10 (10 per 100)

Problem 4

Calculate SMR if observed deaths = 150 and expected = 120.

Answer: SMR = 150/120 = 1.25

Problem 5

Calculate NNT if ARR = 0.04.

Answer: NNT = 1/0.04 = 25

Problem 6

Calculate herd immunity threshold for influenza (Rโ‚€ = 1.8).

Answer: HIT = 1 - 1/1.8 = 44.4%

Problem 7

Calculate attributable fraction if Ie = 0.20 and Iu = 0.05.

Answer: AF = (0.20 - 0.05)/0.20 ร— 100% = 75%

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