---

PSM Epidemiology - Comprehensive Overview

---

1. Definition of Epidemiology

• Distribution - describing who is affected (Person, Place, Time)
• Determinants - identifying causes/risk factors (Analytical epidemiology)
• Application - using findings to prevent/control disease

---

2. Aims of Epidemiology (IEA, International Epidemiological Association)

---

3. Epidemiology vs. Clinical Medicine

"Clinicians are interested in cases with disease, the statistician in the population from which cases are derived, and the epidemiologist is interested in the relationship between cases and the population in the form of a rate."

---

4. Epidemiological Triad (Agent - Host - Environment)

• Agent: Biological (bacteria, viruses), chemical (toxins, tobacco), physical (radiation), nutritional deficiencies
• Host: Immunity, genetics, age, sex, exposure level, nutritional status
• Environment: Surroundings external to the host - physical, biological, socioeconomic
• Time: Accounts for incubation period, duration of illness, life expectancy

---

5. Uses of Epidemiology

1. To study the history of the health of populations and rise/fall of diseases
2. Diagnosis of the health of the community
3. Study of the working of health services
4. Estimation of individual risks from group data
5. Identification of syndromes
6. Completing the clinical picture of chronic diseases
7. Search for causes - identifying risk factors
8. Planning and evaluation of health services

---

6. Basic Measurements in Epidemiology

Rate vs. Ratio vs. Proportion

---

7. Incidence

"The number of NEW cases occurring in a defined population during a specified period of time."

Incidence Rate = (Number of new cases in a given period / Population at-risk in that period) × 1000

• Refers only to new cases
• Measured over a given time period (usually 1 year)
• Denominator = population at-risk
• Used mainly for acute conditions
• Not influenced by duration of disease

Special Incidence Rates

Attack Rate = (New cases of disease / Population at-risk at start of epidemic) × 100

• Used during epidemics when exposure is for a limited period
• Expressed as a percentage

SAR = (New cases among contacts of primary case / Total susceptible contacts) × 100

• Measures the infectivity (communicability) of a disease
• Important index of person-to-person spread

---

8. Prevalence

"The number of ALL cases (new + old) of a disease existing in a given population at a given point in time (or during a period of time)."

Types of Prevalence

---

9. Relationship Between Incidence and Prevalence

• P = Prevalence
• I = Incidence
• D = Average duration of disease

• High prevalence can result from high incidence OR long duration (e.g., TB)
• Low prevalence despite high incidence = short duration (rapid recovery or rapid death, e.g., food poisoning, homicides)
• Improvements in treatment → decrease duration → decrease prevalence
• Treatment that prevents death but doesn't cure → paradoxically increases prevalence

"Prevalence has been compared with a photograph (instantaneous record); incidence with a film (continuous record)."

---

10. Types of Epidemiological Studies

A. Descriptive Studies

• Who gets the disease? (Age, sex, occupation, habits)
• Where does it occur? (International, national, rural-urban, local variations)
• When does it occur? (Secular trends, seasonal variation, cyclical, point epidemic)

B. Analytical Studies

1. Case-Control (Retrospective) Studies

• Start with cases (with disease) and controls (without disease)
• Look backwards to identify prior exposure
• Measure: Odds Ratio (OR)
• Good for: rare diseases, diseases with long latency

2. Cohort (Prospective) Studies

• Start with exposed and unexposed groups (free of disease)
• Follow forward in time to see who develops disease
• Measure: Relative Risk (RR) and Attributable Risk (AR)

• Indicates the excess risk due to exposure
• Important for public health action

• Indicates the amount of disease in the population attributable to the exposure

Comparison of Study Types

C. Experimental (Interventional) Studies

• Investigator controls and manipulates the conditions
• Deliberate application or withdrawal of suspected cause
• Most important type: Randomized Controlled Trial (RCT)

---

11. Randomized Controlled Trials (RCTs)

1. Protocol - define eligibility criteria, endpoints, statistical plan
2. Selecting reference and experimental populations
3. Randomization - random allocation to experimental and control groups
   • Eliminates selection bias and distributes confounders equally
   • Types: Simple, Systematic, Stratified, Cluster randomization
4. Manipulation - apply intervention (drug, vaccine, etc.)
5. Follow-up - observe outcomes in both groups
6. Assessment - compare outcomes

• Single blind: Subject unaware of allocation
• Double blind: Both subject and observer unaware
• Triple blind: Subject, observer AND analyst unaware

• Parallel group design
• Cross-over design
• Factorial design
• Community trials (field trials)

---

12. Descriptive Epidemiology - Person, Place, Time

Person

• Age: Most important host factor. Disease rates vary greatly with age (e.g., infant mortality, geriatric diseases)
• Sex: Biological differences in susceptibility; behavioural differences in exposure
• Race/Ethnicity: Genetic predisposition + socioeconomic + cultural factors
• Occupation: Occupational exposures (silicosis in miners, etc.)
• Marital status, religion, customs, habits (e.g., smoking, diet)
• Socioeconomic status

Place

• International variations (e.g., stomach cancer high in Japan; oral cavity cancer high in India)
• National variations (e.g., distribution of goitre, leprosy, malaria in India)
• Rural-urban variations (e.g., lung cancer, CVD more urban; zoonotic diseases more rural)
• Local distributions (spot maps, shaded maps)

Time

• Short-term fluctuations: Point epidemics, common-source epidemics
• Seasonal variation: Respiratory infections in winter; diarrhoeal diseases in summer
• Cyclical trends: Epidemic cycles (e.g., measles every 2-3 years before vaccination)
• Secular (long-term) trends: Gradual changes over decades

---

13. Types of Epidemics

A. Common-Source Epidemics

• Exposure brief and simultaneous
• All cases develop within one incubation period
• Epidemic curve: rapid rise and fall, single peak
• Example: Food poisoning at a party

• Ongoing exposure from the same source
• Cases continue to appear as long as exposure continues
• Example: Contaminated water supply

B. Propagated Epidemics

• Spread person-to-person, through arthropod vectors, or animal reservoirs
• Epidemic curve: slow rise, multiple peaks, one incubation period apart
• Example: Measles, influenza

C. Slow (Modern) Epidemics

• Gradual rise over decades (e.g., obesity epidemic, tobacco-related cancers, HIV/AIDS in early days)

---

14. Herd Immunity

• Resistance of a group or community to invasion and spread of an infectious agent due to immune individuals in the group
• The higher the proportion immune, the less likely transmission to susceptible individuals
• Herd immunity threshold varies by disease (e.g., measles requires ~92-95% immunity)

---

15. Natural History of Disease & Levels of Prevention

Natural History

• Pre-pathogenesis phase: Before disease onset; interaction of agent, host, environment
• Pathogenesis phase: From first pathological changes to the outcome (recovery, disability, death)

Levels of Prevention (Leavell and Clark)

---

16. Screening

1. Condition should be an important health problem
2. Natural history of condition should be well understood
3. There should be a recognizable latent or early symptomatic stage
4. Effective treatment available
5. Suitable test or examination available
6. Test should be acceptable to the population
7. Policy on who to treat must be agreed upon
8. Facilities for diagnosis and treatment should be available
9. Cost of case-finding must be economically balanced
10. Case-finding should be a continuing process

Validity of Screening Tests

• Sensitivity = TP / (TP + FN) × 100 - ability to detect true cases (pick up all cases, reduce FN)
• Specificity = TN / (TN + FP) × 100 - ability to exclude non-cases (reduce FP)
• Predictive Value Positive (PVP) = TP / (TP + FP) × 100
• Predictive Value Negative (PVN) = TN / (TN + FN) × 100

• As sensitivity ↑, specificity ↓ (inverse relationship - tradeoff)
• PVP depends on prevalence of disease in the population

---

17. Causation in Epidemiology

Web of Causation (MacMahon)

• Disease does not result from a single cause but from a complex interplay of multiple factors
• Identifies multiple entry points for prevention

Hill's Criteria of Causation (Bradford Hill, 1965)

1. Strength of association (high RR or OR)
2. Consistency (same result across different populations, times, studies)
3. Specificity (one cause → one disease)
4. Temporality (cause precedes effect - MOST IMPORTANT)
5. Biological gradient (dose-response relationship)
6. Biological plausibility (makes biological sense)
7. Coherence (consistent with known natural history/biology)
8. Experiment (reversal of exposure reduces disease)
9. Analogy (similar factors cause similar diseases)

Temporality is the only absolute criterion - cause must always precede effect.

---

18. Bias and Confounding

Types of Bias

• Selection bias: Systematic error in selecting study participants (more common in case-control)
• Information bias / Recall bias: Differential recall of exposure between cases and controls
• Observer bias: Systematic error by the observer
• Berkson's bias: Hospital admission rates differ between exposed and unexposed

Confounding

• A confounding variable is associated with both the exposure and the outcome
• Distorts the true relationship between exposure and disease
• Controlled by: Randomization, matching, restriction, stratification, multivariate analysis

---