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Disease = Product of Interplay between:

1. Host

• The person who gets the disease
• Factors: age, sex, immunity, genetics, nutrition, habits

2. Agent

• The cause of disease (biological, chemical, physical, nutritional, mechanical)
• e.g., bacteria, virus, toxin

3. Environment

• External conditions that influence the host-agent interaction
• Physical, biological, social, economic environment

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What "Interplay" Means:

Classic example: Tuberculosis

• Agent: Mycobacterium tuberculosis (always present)
• But disease occurs only when: Host immunity is low + Environment is overcrowded/poor ventilation
• All three must interact unfavorably for disease to manifest

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Related Concept - Leavell & Clark's Model:

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PQLI - Physical Quality of Life Index

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Definition

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Components (3 indicators):

Memory tip: ILL - IMR, Life expectancy (at age 1), Literacy

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How PQLI is Calculated:

• Worst performance = 1
• Best performance = 100

• Maximum possible score = 100
• Higher score = Better quality of life

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Reference Values Used for Indexing:

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Key Points for Exam:

• PQLI does NOT include income/GNP - this is its key feature
• Life expectancy is measured at age 1, not at birth
• Scale: 1 to 100 (not 0 to 100)
• Developed in 1979 by Morris
• India's PQLI has been relatively low compared to developed nations
• It is a simple, easy to calculate composite index

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Criticism of PQLI:

• Only 3 indicators - too few to capture full quality of life
• Doesn't include income, nutrition, sanitation, political freedom
• Later replaced/supplemented by HDI (Human Development Index) by UNDP (1990) which uses: Life expectancy at birth + Education + Per capita income

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India's PQLI

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Context:

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Why India's PQLI is Low:

• High IMR (though improving over decades)
• Lower life expectancy compared to developed nations
• Literacy rate, while improving, still has gaps especially in rural areas and among women

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Important Caveat for Your Exam:

PQLI is an older index (1979) and India's actual indicators have improved significantly over the years. Different editions of textbooks may quote slightly different figures depending on the year of data.

• India's PQLI = 43 (as per Park's Textbook of Preventive & Social Medicine)

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QALY - Quality Adjusted Life Year

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Definition

"One QALY = One year of life lived in perfect health"

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The Formula:

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Simple Example:

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Purpose / Uses:

1. Health economic evaluations - to compare different treatments
2. Cost-utility analysis - Cost per QALY gained
3. Priority setting in healthcare resource allocation
4. Comparing interventions across different disease areas
5. Used by bodies like NICE (UK) for drug approval decisions

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Cost per QALY (Cost-Utility Analysis):

• If an intervention costs less per QALY → more cost-effective
• NICE (UK) threshold: interventions costing < £20,000-30,000 per QALY are considered cost-effective

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How Utility is Measured:

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Related Measure - DALY (compare with QALY):

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Key Exam Points:

• 1 QALY = 1 year of perfect health
• Utility ranges from 0 (death) to 1 (perfect health)
• Used in cost-utility analysis
• Higher QALY gain = better intervention
• DALY = burden (bad); QALY = benefit (good) - opposite directions

Rate, Ratio, and Proportion - Differences

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1. RATIO

Definition:

The numerator is NOT necessarily included in the denominator - this is the key feature!

Examples:

• Sex ratio = Males / Females (e.g., 950 females per 1000 males)
• Maternal mortality ratio
• Case fatality ratio
• Fetal death ratio

Key Feature:

• Numerator and denominator are different/independent groups
• No time dimension required
• Can be expressed as X:Y

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2. PROPORTION

Definition:

Always expressed as a percentage (%) or fraction between 0 and 1.

Examples:

• Proportional mortality rate = (Deaths from disease X / Total deaths) × 100
• Attack rate = (Cases / Population at risk) × 100
• Prevalence = (Existing cases / Total population) × 100

Key Feature:

• Numerator is part of the denominator
• Always between 0 and 1 (or 0-100%)
• Has no time dimension (usually)

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3. RATE

Definition:

Must have a time element - this distinguishes rate from proportion.

Examples:

• Incidence rate = (New cases / Population at risk) × 1000 per year
• Birth rate = (Live births / Mid-year population) × 1000 per year
• Death rate = (Deaths / Population) × 1000 per year

Key Feature:

• Time dimension is mandatory
• Measures speed/frequency of occurrence
• Has a multiplier (per 1000, per 100,000 etc.)

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Summary Comparison Table:

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Classic Exam Trick - "Rates that are actually proportions":

• Attack rate → actually a proportion
• Prevalence rate → actually a proportion
• Case fatality rate → actually a proportion
• Maternal mortality rate → actually a ratio

Examiners love asking: "Which of the following is a true rate?" Answer: Incidence rate (has time dimension) is a true rate.

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Memory Tip:

• Ratio - Relative comparison, numerator Removed from denominator
• Proportion - Part of whole, numerator Part of denominator
• Rate - Rapidity over Real time

Epidemiological Indices - Complete Guide

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A. MEASURES OF DISEASE FREQUENCY

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1. INCIDENCE

Definition:

Formula:

Types:

Example:

• 50 new TB cases in a population of 10,000 in one year
• Incidence = 50/10,000 × 1000 = 5 per 1000 per year

Key Points:

• Measures risk of developing disease
• Requires follow-up over time
• Used in cohort studies
• Reflects speed of disease spread

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2. PREVALENCE

Definition:

Types:

Formula:

Example:

• 200 TB cases (new + old) in population of 10,000
• Prevalence = 200/10,000 × 1000 = 20 per 1000

Key Points:

• Measures burden of disease
• Useful for planning health services
• Used in cross-sectional studies
• Affected by incidence AND duration of disease

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3. RELATIONSHIP: Incidence vs Prevalence

Key Difference:

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B. MEASURES OF ASSOCIATION

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4. RELATIVE RISK (RR) - Risk Ratio

Definition:

Formula:

Using 2×2 Table:

                Disease+    Disease-
Exposed           a            b
Not Exposed       c            d

Interpretation:

Example:

• Smokers: 80 lung cancer cases out of 1000
• Non-smokers: 10 lung cancer cases out of 1000
• RR = (80/1000) / (10/1000) = 8
• Smokers have 8 times the risk of developing lung cancer

Key Points:

• Used in cohort studies
• Cannot be calculated in case-control studies
• Best measure of strength of association

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5. ODDS RATIO (OR)

Definition:

Formula using 2×2 table:

                Disease+    Disease-
Exposed           a            b
Not Exposed       c            d

When to use:

• Case-control studies (RR cannot be calculated)
• Rare diseases (OR approximates RR when disease is rare - rare disease assumption)

Interpretation: Same as RR

• OR = 1 → No association
• OR > 1 → Risk factor
• OR < 1 → Protective

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6. ATTRIBUTABLE RISK (AR) - Risk Difference

Definition:

Formula:

Example (from above):

• AR = 80/1000 - 10/1000 = 70 per 1000
• 70 cases per 1000 are attributable to smoking

Population Attributable Risk (PAR):

• Useful for public health policy - how much disease would be prevented if exposure removed

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7. ATTRIBUTABLE RISK PERCENT (AR%)

• Tells what % of disease in exposed is due to exposure
• Example: AR% = 70/80 × 100 = 87.5% of lung cancer in smokers is due to smoking

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Complete Summary Table:

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Exam Favourite Points:

1. RR is used in cohort studies; OR is used in case-control studies
2. OR approximates RR when disease is rare (rare disease assumption)
3. Prevalence = Incidence × Duration (P = I × D)
4. AR tells public health importance; RR tells biological/causal strength
5. RR and OR both = 1 means no association
6. Attack rate = cumulative incidence used in outbreak investigation
7. Secondary attack rate (SAR) = new cases among contacts / total susceptible contacts