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Chapter 2: Principles of Epidemiology (Study Designs, Outbreak Investigation, Association & Bias) & IMMUNIZATION

WBUHS Exam-Oriented Comprehensive Answers - Based on Park's Textbook of Preventive and Social Medicine

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PART A: OUTBREAK INVESTIGATION QUESTIONS

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Q1. Define "Epidemic" [2 Marks] - Tamralipto GMC

• Derived from Greek: Epi (upon) + demos (people)
• The number of cases indicating epidemic varies with the agent, population size, previous exposure, and time/place of occurrence
• Epidemicity is relative to the usual frequency of the disease in the same area, same population, same season

Key point: Even a single case of a disease long absent from a population (e.g., smallpox) may be considered an epidemic requiring full field investigation. Two cases of such disease associated in time and place may be sufficient.

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Q2. Epidemic vs Outbreak - Define Outbreak, Difference [Burdwan/IQ City/Midnapore]

85 cases of acute diarrhoeal disease in 3 days following a community feast = This is an OUTBREAK (localised to one community event) that may also be called a point-source epidemic since cases arise from a single exposure (the feast).

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Q3. Steps of Epidemic/Outbreak Investigation [6-8 Marks] - Tamralipto, Burdwan, IQ City, Midnapore

• Confirm that cases have the same clinical presentation (vomiting, diarrhoea, abdominal pain)
• Collect stool samples, vomitus, blood from cases for microbiological examination (culture for Salmonella, Vibrio, E. coli, Staphylococcus)
• Rule out other causes of illness

• Compare current case count with baseline/expected frequency for the area
• Establish the epidemic threshold - is the number in excess of normal expectancy?

• Frame an operational case definition based on clinical features, time, place, person
• Example: "Any person who attended the community feast on [date] and developed diarrhoea (3+ loose stools/day) ± vomiting within 72 hours"

• Active case finding by house-to-house survey in the village
• Prepare line listing: name, age, sex, symptoms, date of onset, food items consumed at feast, outcome
• Calculate Attack Rate (AR) = (Number of cases / Population at risk) x 100

• Time: Draw an epidemic curve (histogram of cases by time of onset)
  • Point-source outbreak: bell-shaped curve with narrow peak (single incubation period)
• Place: Spot map of cases - cluster at feast location confirms point-source
• Person: Age, sex, food items consumed - to identify the vehicle

• Based on descriptive data: "Contaminated food item X served at the feast caused the outbreak"
• Food items most likely associated with gastroenteritis: rice, meat, sweets, water

• Conduct a Retrospective Cohort Study (since the exposed population = feast attendees is identifiable)
• Compare attack rates among those who ate specific food items vs. those who did not
• Calculate Relative Risk (RR) and Chi-square for each food item
• The food with highest RR and statistically significant association is the likely vehicle

Why Retrospective Cohort (not Case-Control)? Because the exposed group (feast attendees) is well-defined and enumerable, making cohort study feasible and more efficient.

• Does the food item fit the incubation period? (e.g., Staphylococcal toxin: 1-6 hours; Salmonella: 6-72 hours)
• Does the epidemic curve match the incubation period of suspected agent?

• Inspect the kitchen/food preparation area
• Collect food samples for laboratory analysis
• Check water source used for cooking
• Assess food handlers' health (nasal/throat/stool culture if Staph suspected)

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Q4. Define "Attack Rate" and Calculate It [4 Marks] - Barasat GMC

AR = (Number of persons developing the disease / Number of persons exposed to risk) × 100

• Total village population = 1,500
• Cases of acute watery diarrhoea within 48 hours = 45

Note: If only feast attendees are counted as "exposed population," AR would be higher. AR should ideally be calculated among those exposed to the suspected source (feast attendees), not the total village population.

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Q5. Epidemic Curve - Draw and Interpret [3 Marks] - IQ City

• X-axis: Time of onset of illness (by date/hour)
• Y-axis: Number of cases

• Expected: Point-source epidemic curve - sharp bell-shaped peak within 1-2 days, then rapid decline
• This indicates a single exposure event (the feast) causing illness

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Q6. Immediate Control Measures During Outbreak Investigation [2-5 Marks]

1. Treatment of cases: Oral rehydration therapy (ORT)/IV fluids for dehydration; appropriate antibiotics (Cotrimoxazole/Ciprofloxacin for bacterial causes)
2. Isolate suspected food vehicle: Remove suspected contaminated food items from circulation; stop consumption of food from feast
3. Safe water supply: Chlorination of water source; advise boiling of drinking water; distribute ORS packets
4. Sanitation: Ensure proper disposal of vomitus and excreta; disinfect contaminated surfaces
5. Notify: Report to District Health Officer/CMO; activate surveillance
6. Set up treatment camp: Deploy medical team to affected village, PHC to handle surge
7. Food handler screening: Remove symptomatic food handlers from duty

1. Improve village water supply - piped treated water/deep tube wells
2. Construction of sanitary latrines (Swachh Bharat Mission)
3. Solid waste management and proper drainage
4. Health education on personal hygiene (hand washing, food handling, boiling water)
5. Strengthen food safety regulations for community feasts
6. Regular water quality testing

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Q7. Hepatitis A Outbreak Investigation - Block X [2+5+3 Marks] - College of Medicine & Sagore Dutta

• Children aged 5-10 years (most susceptible age group)
• Exposure to street food (fuchka, velpuri, jhalmuri) at village fair - contaminated food/water
• Classic presentation: fever, loss of appetite, nausea, jaundice (yellowish eyes and skin)
• 2-week incubation period of Hepatitis A (range 15-50 days) matches timeline
• Fecal-oral route transmission via contaminated food/water from street vendors

1. Verify diagnosis: LFT (elevated bilirubin, ALT), serology (anti-HAV IgM)
2. Confirm epidemic: compare with baseline hepatitis cases in the block
3. Case definition: "Any child aged 5-10 presenting with fever, jaundice, raised ALT after attending the fair"
4. Count cases, prepare line listing
5. Descriptive epidemiology (time, place, person) - epidemic curve; spot map; food stalls visited
6. Hypothesis: specific food stall/food item is the vehicle
7. Analytical study (case-control): compare food item exposure between cases and matched controls
8. Environmental: inspect food stalls, water sources, hand-washing facilities at fair
9. Laboratory: stool and water samples; test food handlers' serology

• Treat cases: rest, supportive care, avoid hepatotoxic drugs
• Closure/sanitization of implicated food stalls
• Safe water supply for vendors; mandatory hand-washing at food stalls
• Health education to children, parents, and food vendors
• Active surveillance for new cases
• Post-exposure prophylaxis: Immunoglobulin for close contacts if available

• Hepatitis A vaccination for children in the district (now in some state immunization programs)
• Licensing and regular inspection of food vendors at fairs
• Compulsory provision of hand-washing facilities at public gatherings
• Water quality monitoring
• Inclusion of food safety in school health curriculum

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PART B: EPIDEMIOLOGICAL STUDY DESIGNS

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Q8. Define Epidemiology & Classify Epidemiological Studies [2+3+5 = MCK, Jagannath Gupta]

"Epidemiology is the study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to the prevention and control of health problems." - Last (2001)

EPIDEMIOLOGICAL STUDIES
│
├── OBSERVATIONAL (No intervention)
│   ├── DESCRIPTIVE
│   │   ├── Case Report / Case Series
│   │   ├── Cross-sectional Study (Prevalence Study)
│   │   └── Ecological (Correlational) Study
│   │
│   └── ANALYTICAL
│       ├── Case-Control Study (Retrospective)
│       └── Cohort Study (Prospective / Retrospective)
│
└── EXPERIMENTAL (Intervention)
    ├── Randomized Controlled Trial (RCT)
    ├── Field Trial
    └── Community Trial

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Q9. Cross-Sectional Study - For Prevalence of Obesity Among Medical Students [2+13 = 15, Barasat GMC]

• Short duration (3 months) - feasible within the time frame
• Objective is to measure prevalence (not incidence or causal relationship)
• All measurements made at a single point in time
• Appropriate for common conditions like obesity

1. Define study population: All medical students of the institution (Phase 1, 2, 3)
2. Sampling: Calculate sample size using formula: n = Z²pq/d² (where p = estimated prevalence ~30%, d = desired precision 5%)
   • Use Stratified Random Sampling (stratify by batch/year, then random within each stratum)
3. Prepare data collection tool: Structured questionnaire covering:
   • Demographic details (age, sex, year of study)
   • Dietary habits, physical activity, screen time
   • Clinical measurements: weight, height, waist circumference
4. Define Obesity: BMI ≥ 25 kg/m² (Asian cut-off) or WHO ≥ 30 kg/m²
5. Collect data: Physical examination (height by stadiometer, weight by calibrated scale)
6. Calculate BMI = Weight (kg) / Height (m)²
7. Data entry and analysis: SPSS/Epi Info
   • Calculate prevalence of obesity (overall, by sex, by year)
   • Chi-square test for association with dietary habits, physical activity
8. Report findings

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Q10. Cohort Study - For Nuclear Plant Radiation Workers / Radiation & Silicosis / Obesity-Hypertension [JNM Kalyani, RGKMC, Deben Mahata]

• Exposure is well-defined (radiation workers, obese individuals)
• Study proceeds from cause to effect (forward direction)
• Incidence rates and Relative Risk (RR) can be calculated directly
• Temporal relationship between exposure and disease is established
• Ethical to study harmful exposures by observation (not experimentation)

• Exposed group (Cohort 1): Workers in nuclear plant with documented radiation exposure (dosimetry records) / Obese individuals (BMI ≥ 25)
• Unexposed group (Cohort 2): Workers in same plant with no radiation exposure / Non-obese individuals (BMI < 25)
• Both groups must be free of the disease (cancer/hypertension) at the start
• Match for age, sex, smoking status, other confounders

• Detailed exposure measurement (radiation dosimetry/BMI at baseline)
• Baseline health examination, investigations (blood tests, BP, etc.)
• Sociodemographic data, lifestyle factors

• Follow both cohorts for the specified period (5 years for radiation study; 15 years for obesity-hypertension)
• Periodic health check-ups at defined intervals
• Monitor for development of outcome (cancer, hypertension, silicosis)
• Track dropouts and withdrawals (minimize attrition)

• Standardized criteria for disease diagnosis
• Blind assessment of outcome to prevent observer bias

• Calculate Incidence Rate in exposed and unexposed groups
• Calculate Relative Risk (RR) = Incidence in exposed / Incidence in unexposed
• Calculate Attributable Risk (AR) = Incidence in exposed - Incidence in unexposed

• 2000 obese individuals: 200 developed hypertension → Incidence = 200/2000 = 0.10 (10%)
• 4000 non-obese: 100 developed hypertension → Incidence = 100/4000 = 0.025 (2.5%)
• RR = 0.10 / 0.025 = 4.0
• Interpretation: Obese individuals have 4 times the risk of developing hypertension compared to non-obese individuals

1. Establishes temporal relationship (exposure precedes disease)
2. Directly measures incidence rates
3. Can study multiple outcomes of one exposure
4. Less susceptible to selection and recall bias
5. Gold standard for establishing causation
6. RR can be calculated directly

1. Time-consuming and expensive
2. Large sample size required
3. Inappropriate for rare diseases (need very large cohort to detect cases)
4. Attrition/loss to follow-up is a major problem
5. Changes in diagnostic criteria over time
6. Healthy worker effect may bias results
7. Exposure levels may change over time

• Selection bias: Healthy worker effect (workers are healthier than general population)
• Attrition bias: Loss to follow-up may be differential (those who develop disease may be lost)
• Information bias: Changes in diagnostic criteria, observer bias in outcome assessment
• Confounding: Age, smoking, diet may confound the relationship

"Cohort study is the gold standard for establishing temporal association, but inappropriate for finding risk factors of a rare disease" - because for rare diseases, the cohort would need to be enormous to accumulate enough cases, making it impractical and expensive. Case-control study is preferred for rare diseases.

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Q11. Case-Control Study - Obesity & Osteoarthritis / OCP & Breast Cancer [PC Sen, ESI Joka]

• The disease (osteoarthritis) may already be present
• Proceeds from effect to cause (backward direction)
• Suitable for studying rare diseases and diseases with long latency
• Can study multiple risk factors simultaneously

• Cases: Persons aged 35-65 years diagnosed with osteoarthritis of the knee joint (by clinical + radiological criteria - Kellgren-Lawrence grade ≥ 2)
• Source: Orthopaedic OPD/hospital records

• Persons aged 35-65 years without osteoarthritis of the knee
• Matched to cases for age (±5 years), sex, socioeconomic status
• Source: Same hospital (other OPD) or community
• Ratio: 1:1 or 1:2 (case:control)

• Measure BMI (current and recall of past weight/BMI)
• Detailed history: occupation, physical activity, diet, joint injuries, family history
• Standardized questionnaire administered by blinded interviewer

              Cases    Controls
Obese (Exposed)    a        b
Non-obese          c        d

OR = (a×d) / (b×c)

• OR >1: Obesity associated with increased risk of OA
• Statistical significance by Chi-square or 95% CI not including 1

1. Relatively quick and inexpensive
2. Suitable for rare diseases
3. Can study multiple risk factors simultaneously
4. Small sample size required
5. No attrition problem (no follow-up)
6. Ethical - no intervention
7. Good for diseases with long latency

1. Susceptible to recall bias (cases recall exposure differently than controls)
2. Susceptible to selection bias (cases and controls may not represent general population)
3. Cannot calculate incidence or RR directly (only OR)
4. Cannot study rare exposures
5. Temporality may be uncertain
6. Berkesonian bias (hospital-based studies)
7. Cannot study multiple outcomes of a single exposure

1. Recall/Memory Bias: Cases more likely to recall past exposures than controls (differential misclassification)
2. Selection Bias: Non-representative selection of cases and controls
3. Berkesonian Bias: Hospital cases and controls have different admission rates for different diseases
4. Interviewer Bias: Knowledge of case/control status influences depth of questioning
5. Confounding Bias: Variables correlated with both exposure and outcome (e.g., age, sex, occupation in OA study)

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Q12. Cohort Study - OCP and Breast Cancer Causal Association [ESI Joka] / Screen Time & Mental Health [COM Sagore Dutta]

• Long latency of breast cancer requires long follow-up - cohort is ideal
• Exposure (OCP use) can be prospectively documented and quantified (dose, duration)
• Can calculate incidence and RR directly
• Establishes temporal relationship (OCP use precedes cancer)
• However, a case-control study is also acceptable and more practical

• Ethically unacceptable to randomly assign women to OCP exposure to study cancer risk

• Exposed cohort: Women using OCP for >5 years
• Unexposed cohort: Women never using OCP, matched for age, parity, family history
• Follow up for 10-15 years
• Outcome: New diagnosis of breast cancer (confirmed histologically)
• Calculate RR

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Q13. Randomized Controlled Trial (RCT) - Comparing Two Drugs for Hypertension [IQ City]

1. Frame the Research Question: Is Drug A superior to Drug B in reducing blood pressure in hypertensive patients?
2. Define eligibility criteria: Inclusion (newly diagnosed hypertension, age 30-60, no secondary HTN) and Exclusion criteria
3. Calculate sample size: Based on expected difference in BP reduction, alpha (0.05), power (80%)
4. Recruit participants: Obtain informed consent
5. Randomization: Randomly allocate participants to Drug A or Drug B using computer-generated random numbers or sealed envelopes
6. Blinding:
   • Double-blind: neither participant nor investigator knows which drug is administered
   • Use identical-appearing tablets (placebo or active)
7. Intervention: Administer drugs for defined period (e.g., 6 months)
8. Follow-up: Regular BP measurements, compliance assessment, adverse event monitoring
9. Outcome assessment: Change in systolic/diastolic BP at 6 months; blinded assessors
10. Analysis: Intention-to-treat analysis; calculate mean difference in BP between groups; paired t-test or ANOVA

• Randomization: Ensures comparable distribution of known and unknown confounders between groups; prevents selection bias at allocation
• Blinding: Prevents performance bias (investigator treating groups differently) and detection/assessment bias (observer knowing group assignment influences outcome measurement)
• Randomization ensures groups are comparable at baseline; blinding ensures groups are treated and assessed comparably throughout the study

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Q14. Relative Risk (RR) - Calculation [Diamond Harbour GMC&H]

RR = Incidence in exposed / Incidence in unexposed = [a/(a+b)] / [c/(c+d)]

• Incidence in exposed = 120/800 = 0.15 (15%)
• Incidence in unexposed = 30/1200 = 0.025 (2.5%)
• RR = 0.15 / 0.025 = 6.0

• RR (Relative Risk): Ratio of incidences; measures strength of association; useful for etiology
• AR (Attributable Risk = Absolute Risk Difference): Difference of incidences (Incidence in exposed - Incidence in unexposed); measures public health impact; useful for prevention
• AR in above example = 15% - 2.5% = 12.5% (12.5% of silicosis in exposed workers is attributable to silica dust exposure)

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Q15. Bias and Confounding - Not Synonymous [CNMC]

• Bias leads to a wrong conclusion that is consistently in one direction
• Cannot be corrected after data collection (selection, information, recall bias)
• Example: Recall bias in case-control study

1. Associated with the exposure
2. Independently associated with the disease
3. Not an intermediate step in the causal pathway

• Example: Alcohol (exposure) - liver disease (outcome); but smoking is a confounder (smokers drink more AND smoking independently causes liver disease)
• Confounding can be controlled (by matching, stratification, multivariate analysis, RCT randomization)

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Q16. Epidemic Curve Types / Time Trends in Disease [RGKMC]

1. Point-Source Epidemic: All cases exposed to a common source at the same time; incubation periods overlap; produces a unimodal bell-shaped curve; ends within one incubation period
   • Example: Food poisoning at a feast
2. Continuous/Propagated Source Epidemic: Ongoing exposure from a common source OR person-to-person spread; multiple peaks, each peak representing one generation time
   • Example: Cholera from contaminated water supply; measles in a school
3. Mixed Epidemic: Initially point-source, then propagated by person-to-person spread
   • Example: Initial food-borne Salmonella then spread between household contacts

• Secular trend (long-term): Change over decades - e.g., decline of smallpox after vaccination
• Cyclical/Periodic trend: Regular periodic fluctuations - e.g., influenza every few years
• Seasonal trend: Regular variation with seasons - e.g., cholera in monsoon, measles in winter/spring
• Point epidemic (short-term): Sudden sharp rise and fall over days/weeks

• Changes in reporting system/completeness
• Changes in case definition or diagnostic criteria
• Changes in population demographics
• Changes in environmental or social conditions
• Artefactual changes (improved surveillance detecting more cases)

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Q17. Descriptive Epidemiology - Person, Place, Time & Point Source Epidemic [IPGMER]

1. All cases exposed to a common source at approximately the same time
2. Cases cluster in a single peak on the epidemic curve
3. Duration of epidemic spans approximately one incubation period
4. Attack rates are high among the exposed
5. When the source is removed, epidemic ends abruptly
6. Example: Gastroenteritis from a contaminated food item at a feast

• Geographic variation reveals environmental, genetic, or cultural risk factors
• Spot maps show clustering of cases to identify point sources
• International comparisons reveal lifestyle/environmental differences (e.g., high breast cancer in Western countries vs. low in Asia suggests dietary/hormonal differences)
• Migration studies separate genetic from environmental factors

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PART C: IMMUNIZATION QUESTIONS

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Q18. National Immunization Schedule (NIS) for Infant [KPCMCH]

• The birth dose of OPV provides very early mucosal immunity in the gut
• In tropical countries, maternal antibodies and gut infections reduce OPV efficacy; early priming improves response to subsequent doses
• Maximizes opportunity for immunization at birth contact
• Polio eradication strategy requires high coverage, starting as early as possible

• Perinatal (mother-to-child) transmission during delivery accounts for >50% of chronic HBsAg carriers
• HBV can be transmitted during birth from HBsAg-positive mothers (vertical transmission)
• Birth dose given within 24 hours prevents perinatal transmission (90% of babies born to HBeAg+ mothers would become chronically infected without vaccination)
• Window of protection: The vaccine takes 2-4 weeks to generate antibodies; early administration ensures protection before viral replication establishes chronic infection
• A baby infected perinatally has 90% chance of becoming a chronic carrier; chronic carriers have high risk of cirrhosis and hepatocellular carcinoma

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Q19. Adverse Events Following Immunization (AEFI) [Malda, JMN, IPGMER]

• Caused by the inherent properties of the vaccine
• Example: BCG adenitis, Oral poliovirus vaccine-derived paralytic polio (VAPP)

• Due to quality defects in a specific vaccine lot
• Example: Higher reaction rates due to manufacturer error

• Due to inappropriate handling, prescribing, or administration
• Examples:
  • Abscess at injection site (non-sterile technique)
  • Toxic shock syndrome (contaminated multi-dose vial)
  • BCG given subcutaneously instead of intradermally

• Psychological response to immunization (not due to vaccine)
• Example: Vasovagal syncope, hyperventilation

• Events that would have occurred regardless of vaccination
• Example: Fever from another concurrent infection coinciding with vaccination

• Serious AEFI: Meets clinical criteria - death, hospitalization, life-threatening, disability (administrative/regulatory definition)
• Severe AEFI: Refers to intensity/grade of the reaction (Grade 3 or 4 on severity scale)
• A reaction can be serious but not severe (e.g., hospitalization for mild allergic rash) or severe but not serious (e.g., severe pain at injection site not requiring hospitalization)

• Most probable diagnosis: Anaphylaxis (severe allergic reaction to MR vaccine components - gelatin, neomycin)
• Features: Onset within 30 min, breathing difficulty, generalized rash, unconsciousness
• Management: Adrenaline 1:1000 IM (0.01 mg/kg), oxygen, IV fluids, antihistamine, steroids; refer to higher centre
• Investigation at field level: Report to AEFI committee; investigate case; review cold chain and vaccine lot; check if other children from same session had reactions

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Q20. Immunization Drop-Out and Left-Out [Jhargram, RGMC]

• Acceptable drop-out rate: <10%

• Long distance to immunization center
• Fear of side effects
• Long waiting time
• Cultural/religious beliefs
• Previous AEFI in family
• Misinformation
• Health worker attitude/counseling inadequacy
• Service-level issues (vaccine stockouts, broken cold chain)

• Inaccessibility (remote/tribal areas)
• Migrant populations
• Urban slums - transient population
• Poor outreach
• Parents unaware of immunization

1. Outreach sessions - taking immunization to community (mobile teams)
2. Due list preparation - tracking expected beneficiaries
3. Default tracking - reminders via ASHA/ANM for missed doses
4. VHND (Village Health, Nutrition and Sanitation Days) - regular sessions
5. Mission Indradhanush - targeting left-outs and drop-outs
6. Microplanning - identify unreached settlements
7. IEC activities - health education through ASHA, anganwadi workers
8. Open Vial Policy - use opened multi-dose vials in subsequent sessions to reduce wastage

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Q21. HPV Vaccination [CNMC, Midnapore, Santiniketan, Burdwan]

• Cervical cancer is the 2nd most common cancer in women in India (after breast cancer) - hence the statement "HPV vaccination started to prevent second most common cancer among women"
• Human Papillomavirus (HPV) types 16 and 18 cause ~70% of cervical cancers
• HPV types 6 and 11 cause genital warts

• Individual protection: Direct immunity against HPV infection and cervical cancer
• Herd immunity: High vaccination coverage reduces HPV circulation in the community, protecting unvaccinated individuals
• Community/disease load reduction: Even unvaccinated women benefit from reduced HPV transmission when high coverage achieved in the population
• This principle applies to all vaccines - reducing disease load in community (herd immunity) is a major public health objective

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Q22. Population Attributable Risk (PAR) [KPC Medical College]

• Measures public health impact of an exposure
• Indicates what proportion of disease in the total population is attributable to the risk factor
• Guides decisions about which risk factors to target for maximum population benefit
• Differs from AR (Attributable Risk) which applies only to the exposed group

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Q23. Sentinel Surveillance [MCK]

• Uses pre-selected institutions (hospitals, PHCs, labs) with high case load
• Continuous, systematic data collection
• Quality over quantity (in-depth data from fewer sites)
• Less expensive than universal/comprehensive surveillance

• Provides early warning signals of unusual disease activity
• The sentinel sites are strategically located to capture new or re-emerging disease
• Data can trigger rapid response before disease spreads widely
• Example: Sentinel surveillance sites for influenza (FRI surveillance) detect new strains early

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Q24. Monitoring vs Surveillance - Not Synonymous [Jhargram GMC&H]

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Q25. Nested Case-Control Study [MJN Medical College, Coochbehar]

1. Exposure data collected prospectively (reduces recall bias)
2. Controls drawn from the same cohort (reduces selection bias)
3. More efficient than following entire cohort
4. Biological samples stored at baseline can be tested later

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Q26. Cold Chain System in UIP [Malda]

• BCG, OPV: -15°C to -25°C (freezer)
• DPT, Hepatitis B, DT, TT: +2°C to +8°C (refrigerator) - Do NOT freeze these
• OPV: -20°C at district level; +2 to +8°C at PHC level for up to 1 month

1. Walk-in Freezer (WIF) / Walk-in Cooler (WIC) - State/Regional level
2. Deep Freezer (ILR - Ice Lined Refrigerator) - District level
3. Ice-Lined Refrigerators (ILR) - CHC/PHC level
4. Vaccine Carriers / Cold Boxes - Sub-centre / outreach sessions
5. Hub Cutters: Must be present at every immunization session for safe disposal of syringes

• Multi-dose vials of certain vaccines (OPV, DPT, Hepatitis B, TT, DT) that have not been contaminated can be used in subsequent sessions if:
  • Cold chain maintained
  • VVM (Vaccine Vial Monitor) has not reached endpoint
  • Expiry date not passed
  • No visible contamination
• Vaccines NOT covered by open vial policy: BCG, Measles, MR (must be used within 4 hours of reconstitution)

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Q27. Disability vs Handicap - Not Synonymous [SCCMCH]

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Q28. SRS - Sample Registration System [Jhargram GMC&H]

• Established in 1964-65 in India; provides reliable estimates of birth and death rates at national and state level
• Uses dual recording mechanism:
  1. Continuous enumeration by a resident part-time enumerator
  2. Independent half-yearly retrospective survey by a supervisor
  3. Matching of the two sets of records - unmatched events are re-verified in the field
• Provides: Crude Birth Rate (CBR), Crude Death Rate (CDR), Infant Mortality Rate (IMR), Total Fertility Rate (TFR), Age-specific fertility rates
• Why reliable? Uses dual recording, systematic matching, covers both rural and urban areas, large representative sample of villages/urban blocks

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SUMMARY TABLE: Epidemiological Study Designs for WBUHS

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Chapter 2 - Complete WBUHS Answers

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PART A: OUTBREAK INVESTIGATION

Q1. Define "Epidemic" [2 Marks - Tamralipto GMC]

• Greek origin: Epi (upon) + demos (people)
• Epidemicity is relative to usual frequency in same area, same season
• Even a single case of a disease long absent from a population may require full epidemic investigation

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Q2. Epidemic vs Outbreak [1+1 Marks - Burdwan MC / IQ City]

85 cases in 3 days after a feast = OUTBREAK (also a point-source epidemic - single exposure event)

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Q3. Steps of Outbreak/Epidemic Investigation [6-8 Marks - Tamralipto, Burdwan, IQ City, Midnapore, Barasat GMC]

• Time: Draw epidemic curve - histogram of cases by time of onset
  • Single peak (bell-shaped) = point-source; progressive peaks = propagated
• Place: Spot map - cases cluster at feast location
• Person: Age, sex, specific food items consumed

• Compare attack rates among those who ate specific foods vs. those who did not
• Calculate Relative Risk (RR) for each food item
• Food with highest RR + statistical significance = likely vehicle

Why retrospective cohort (not case-control)? The exposed population (feast attendees) is well-defined and enumerable.

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Q4. Define "Attack Rate" and Calculate [4 Marks - Barasat GMC]

AR = (Number of persons developing disease / Number exposed to risk) × 100

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Q5. Epidemic Curve - Draw and Interpret [3 Marks - IQ City]

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Q6. Immediate Control Measures During Investigation [2-5 Marks]

1. ORT / IV fluids for dehydrated cases; antibiotics where indicated (Ciprofloxacin for Vibrio/Salmonella)
2. Remove suspected contaminated food from circulation; stop consumption of feast food
3. Safe water: chlorination; distribute ORS; advise boiling water
4. Sanitation: proper disposal of excreta/vomitus; disinfect contaminated areas
5. Notify District Health Officer/CMO; activate disease surveillance
6. Deploy medical team; set up treatment camp in the village
7. Screen and remove symptomatic food handlers from duty

• Safe piped water supply or deep tube wells
• Sanitary latrines (Swachh Bharat Mission)
• Solid waste management and drainage improvement
• Health education on personal hygiene, hand-washing, food safety
• Regulation of food vendors at community gatherings
• Regular water quality testing

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Q7. Hepatitis A Outbreak - Block X [2+5+3 Marks - College of Medicine & Sagore Dutta]

1. Verify: LFT (↑bilirubin, ↑ALT), serology (anti-HAV IgM)
2. Confirm epidemic, define cases, count and list
3. Epidemic curve + spot map of cases vs. food stalls visited
4. Hypothesis: specific food stall/contaminated water is vehicle
5. Analytical study: Case-control study comparing food stall exposure between cases and matched healthy controls who attended the fair
6. Inspect food stalls: water source, hand-washing facilities, food handler health
7. Laboratory: stool/water samples, food handler serology

• Supportive treatment (rest, IV fluids; avoid hepatotoxins)
• Closure and sanitization of implicated stalls
• Safe water for all vendors; mandatory hand-washing
• Health education to parents, children, vendors
• Active surveillance; post-exposure immunoglobulin for close contacts

• Hepatitis A vaccination in the district
• Licensing, regular inspection, and hygiene certification for food vendors at public gatherings
• Compulsory hand-washing stations at fairs
• Water quality monitoring
• Food safety in school health curriculum

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PART B: EPIDEMIOLOGICAL STUDY DESIGNS

Q8. Define Epidemiology & Classify Studies [2+3 - MCK/Jagannath Gupta]

"Epidemiology is the study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to the prevention and control of health problems."

EPIDEMIOLOGICAL STUDIES
├── OBSERVATIONAL
│   ├── DESCRIPTIVE: Case report, Cross-sectional, Ecological
│   └── ANALYTICAL: Case-Control, Cohort
└── EXPERIMENTAL
    ├── RCT (Randomized Controlled Trial)
    ├── Field Trial
    └── Community Trial

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Q9. Cross-Sectional Study - Prevalence of Obesity Among Medical Students [2+13=15, Barasat GMC]

1. Define study population (all medical students by year)
2. Calculate sample size: n = Z²pq/d² (p ≈ 30%, d = 5%, Z = 1.96 → n ≈ 323)
3. Sampling: Stratified Random Sampling (stratify by year of study, random within each stratum)
4. Prepare questionnaire: demographics, diet, physical activity, screen time
5. Define obesity: BMI ≥ 25 kg/m² (Asian cut-off); measure height (stadiometer) and weight (calibrated scale)
6. Calculate BMI = Weight (kg) / Height (m)²
7. Data entry and analysis (Epi Info/SPSS):
   • Overall prevalence; prevalence by sex and year
   • Chi-square for associations with risk factors
8. Write report with recommendations

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Q10. Cohort Study [Steps, Advantages, Disadvantages, Bias] - JNM Kalyani, MCK, RGKMC, Deben Mahata, COM Sagore Dutta, ESI Joka

1. Selection of cohorts:
   • Exposed cohort: Radiation workers / Obese individuals (BMI ≥ 25) - free of outcome disease at start
   • Unexposed cohort: Non-exposed workers / Non-obese - matched for age, sex, smoking
2. Baseline data collection: Exposure measurement (dosimetry/BMI), baseline health check-ups, investigations
3. Follow-up over defined period (5 years/15 years): periodic examinations; monitor for outcome (cancer/hypertension)
4. Outcome assessment: Standardized diagnostic criteria; blinded assessment
5. Analysis:
   • Incidence rate in exposed and unexposed groups
   • RR = Incidence in exposed / Incidence in unexposed
   • AR = Incidence in exposed - Incidence in unexposed

• Obese: 200/2000 = 10% incidence
• Non-obese: 100/4000 = 2.5% incidence
• RR = 10/2.5 = 4.0 → Obese individuals have 4× the risk of hypertension

1. Establishes temporal relationship (cause precedes effect)
2. Directly measures incidence rates
3. Can study multiple outcomes of one exposure
4. Less susceptible to recall and selection bias
5. Gold standard for causation (after RCT)
6. RR calculated directly

1. Time-consuming and expensive
2. Large sample size needed
3. Inappropriate for rare diseases - need enormous cohort to detect cases; case-control preferred
4. Attrition/loss to follow-up major problem
5. Healthy worker effect may bias occupational studies
6. Changes in diagnostic criteria over follow-up period

• Selection bias: Healthy worker effect
• Attrition bias: Differential loss to follow-up
• Information bias: Changes in diagnostic criteria, observer bias
• Confounding: Age, smoking, diet

"Cohort study is gold standard for temporal association but inappropriate for rare diseases" - because it would need an impractically large cohort and prolonged follow-up to accumulate enough cases of a rare disease.

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Q11. Case-Control Study [Design, Advantages, Disadvantages, Bias] - PC Sen, ESI Joka, MJN Coochbehar, NRS

1. Define cases: OA knee (clinical + radiological: K-L grade ≥ 2), age 35-65 years, from orthopaedic OPD
2. Define controls: Same age range, no OA knee; matched for age (±5 years) and sex; from same hospital (other OPD) or community
3. Obtain exposure data: BMI measurement + recall of past weight; standardized questionnaire (blinded interviewer) on occupation, physical activity, diet, joint injuries
4. Calculate Odds Ratio (OR):

1. Control confounding: Matching, stratification, multivariate logistic regression

1. Quick and inexpensive
2. Suitable for rare diseases
3. Studies multiple risk factors simultaneously
4. Small sample size needed
5. No attrition problems (no follow-up)
6. Ethical - no intervention
7. Good for diseases with long latency period

1. Susceptible to recall/memory bias
2. Susceptible to selection bias
3. Cannot calculate incidence or RR directly (only OR approximates RR for rare diseases)
4. Cannot study rare exposures
5. Temporality may be uncertain
6. Berkesonian bias in hospital-based studies
7. Cannot study multiple outcomes of a single exposure

1. Recall (Memory) Bias - Cases recall past exposure more vividly than controls (differential misclassification)
2. Selection Bias - Cases and controls not representative of general population
3. Berkesonian Bias - Differential hospital admission rates for cases vs. controls with different diseases
4. Interviewer Bias - Awareness of case/control status influences depth of questioning; controlled by double-blinding
5. Confounding Bias - Third variable (age, sex, occupation) distorts observed association

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Q12. Cohort Study for OCP and Breast Cancer / Rare Fatal Disease [ESI Joka, Bankura Sammilani]

• Best design: Case-Control Study - most practical for rare diseases; efficient use of resources
• Steps: identify all available cases of the disease nationally; recruit matched controls; obtain exposure history retrospectively

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Q13. RCT - Two Drugs for Hypertension / Randomization and Blinding [IQ City, Deben Mahata, Barasat GMC]

1. Frame research question: Is Drug A superior to Drug B in reducing BP?
2. Define eligibility criteria (inclusion/exclusion)
3. Calculate sample size (expected BP difference, alpha = 0.05, power = 80%)
4. Recruit, obtain informed consent
5. Randomization: Computer-generated random numbers → allocate to Drug A or B
6. Double-blinding: Identical tablets; neither participant nor investigator knows assignment
7. Administer drugs for 6 months; monitor compliance and adverse events
8. Outcome assessment: BP at 6 months by blinded assessor
9. Analysis: Intention-to-treat; t-test/ANOVA for mean BP difference

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Q14. Relative Risk - Calculation [Diamond Harbour GMC&H]

• Exposed with silicosis: 120/800 = 15%
• Unexposed with silicosis: 30/1200 = 2.5%
• RR = 15/2.5 = 6.0
• Interpretation: Exposed workers have 6× the risk of developing silicosis - strong causal association

• RR: Ratio - measures strength of association (useful for etiology, causation)
• AR (Attributable Risk): Difference - Incidence(exposed) - Incidence(unexposed) = 15% - 2.5% = 12.5% - measures excess risk due to exposure (useful for public health impact, prevention)

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Q15. Bias and Confounding - Not Synonymous [CNMC]

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Q16. Epidemic Curve Types / Time Trends [RGKMC]

1. Point-source: Single common exposure → single bell-shaped peak; ends within one incubation period
2. Propagated: Person-to-person spread → progressive multiple peaks, each = one generation time
3. Mixed: Point-source followed by person-to-person spread

• Secular: Decades-long changes (decline of smallpox, rise of NCD)
• Cyclical/Periodic: Regular fluctuations every few years (influenza, cholera pandemics)
• Seasonal: Regular annual variation (monsoon cholera, winter measles)
• Short-term fluctuations: Sudden point epidemics

• Completeness and changes in reporting system
• Changes in case definition or diagnostic criteria
• Population demographic changes
• Artefactual changes (better surveillance detecting more cases)

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PART C: IMMUNIZATION

Q17. National Immunization Schedule for Infant [KPCMCH]

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Q18. AEFI - Classification, Serious vs Severe [Malda, JMN, IPGMER]

1. Vaccine Product-Related Reaction: Inherent properties of vaccine. Example: VAPP (oral poliovirus), BCG adenitis
2. Vaccine Quality Defect-Related Reaction: Manufacturer defect in a batch. Example: Higher reaction rates from a specific lot
3. Immunization Error-Related Reaction: Improper handling or administration. Examples: Abscess (non-sterile technique), toxic shock (contaminated multi-dose vial), wrong route (BCG subcutaneously)
4. Immunization Anxiety-Related Reaction: Psychological. Example: Vasovagal syncope, hyperventilation, fainting
5. Coincidental Event: Would occur regardless of vaccination. Example: Fever from concurrent viral infection

• Serious: Administrative/regulatory classification - any event resulting in death, hospitalization, life-threatening illness, or permanent disability
• Severe: Intensity grade (Grade 3/4 on clinical severity scale)
• A reaction can be serious but not severe (e.g., hospitalization for mild rash) or severe but not serious (e.g., intense pain at injection site not requiring hospitalization)

• Diagnosis: Anaphylaxis (onset within 30 min, dyspnoea, rash, unconsciousness) - most serious vaccine product-related reaction
• Immediately: Adrenaline (epinephrine) 1:1000 IM (0.01 mg/kg, max 0.5 mg) into anterolateral thigh; oxygen; IV access; antihistamine (chlorphenamine); IV corticosteroids; refer to district hospital
• Investigate: AEFI committee notification; review cold chain; check vaccine lot number; investigate other children from same session

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Q19. Drop-out and Left-out Children [Jhargram, RGMC]

• Outreach sessions (mobile immunization teams)
• Due list preparation and default tracking by ASHA/ANM
• Village Health, Nutrition and Sanitation Days (VHND)
• Mission Indradhanush - targets left-outs and drop-outs
• Microplanning to identify unreached settlements
• IEC activities through ASHA and anganwadi workers
• Open Vial Policy (see below)

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Q20. HPV Vaccination [CNMC, Midnapore, Santiniketan, Burdwan, PC Sen]

• Cervical cancer is the 2nd most common cancer in women in India (hence: "HPV vaccination to prevent second most common cancer")
• HPV types 16 and 18 cause ~70% of cervical cancers
• Vaccines available: Cervarix (bivalent), Gardasil (quadrivalent), Gardasil-9 (nonavalent)
• India's Cervavac (indigenously developed quadrivalent) introduced in NIS 2023
• Target: Girls aged 9-14 years (before sexual debut); 2 doses 6 months apart; IM deltoid

• Direct individual immunity (individual protection)
• Herd immunity - high coverage reduces community HPV circulation, protecting even unvaccinated individuals
• Reduces overall community cancer burden
• Applies to all vaccines: the dual purpose is individual immunity AND community disease load reduction

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Q21. Serious Additional Points

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